Forthcoming

Robustness and vulnerability in organizational process networks: a systemic approach for strategic management

Authors

  • Carmen Hernández-Cansino Universidad Autónoma de Querétaro, Campus Aeropuerto de la UAQ, Carretera a Chichimequillas s/n, Ejido Bolaños, Santiago de Querétaro, Querétaro, México, C. P. 76140. https://orcid.org/0000-0003-1403-5231
  • Gustavo Carreón-Vázquez Universidad Nacional Autónoma de México, Instituto de Investigaciones Económicas, Ciudad de México, México, C. P. 04510. https://orcid.org/0000-0002-6776-4027
  • Alejandra Elizabeth Urbiola-Solís Universidad Autónoma de Querétaro, Facultad de Contaduría y Administración, Querétaro, Querétaro, México, C. P. 76020. https://orcid.org/0000-0001-5782-6215
  • Graciela Carrillo-González Universidad Autónoma Metropolitana, Unidad Xochimilco, UAM-X, Departamento de Producción Económica, Alcaldía Coyoacán, Ciudad de México, México, C. P. 04960. https://orcid.org/0000-0001-8969-5096

DOI:

https://doi.org/10.29059/cienciauat.v20i2.2047

Keywords:

complex networks, robustness, vulnerability, organizational processes, strategic management

Abstract

The methodology for analyzing Complex Adaptive Systems (CAS) is a useful tool for studying work collaboration networks through their structural representation. This approach makes it possible to identify patterns of interaction, dependency, and information flow among the components of these networks. The objective of this study was to identify the conditions of robustness and vulnerability in an organizational process network within an administrative department (DPE) of a public educational institution. A modeling methodology based on criteria of connectivity, centrality, and information-flow efficiency was used. The operational procedures of the different actors were analyzed; the organizational network was constructed by defining its nodes; and the levels of connectivity and stress centrality were evaluated for each node. To measure the level of robustness, node-removal simulations were performed on the nodes with the highest connectivity. The elimination of nodes with high connectivity and stress centrality—such as those corresponding to the Department Administrative Assistant, the Faculty Secretary, and the Technical Assistant, who are responsible for articulating a large part of the DPE’s operational processes—produced the greatest fragmentation of the network. This contrasted with the removal of the Head of the Department, which produced a considerably lower level of fragmentation. The analysis of the functional structure revealed that the robustness of the network is determined by the way in which processes are structured and interconnected, rather than by the formal hierarchy of job positions. The representation of organizational positions as nodes made it possible to identify critical bottlenecks, functional dependencies, and positions whose interruption would compromise operational continuity. The development of the operational diagram and its analysis through the CAS approach made it possible to reveal the system’s strengths and vulnerabilities, providing key information to strengthen organizational robustness, operational continuity, and adaptive capacity from a systemic strategic management perspective.

References

Artime, O., Marco Grassia, M., De-Domenico, M., Gleeson, J. P. Makse, H. A., Mangioni, G., Perc, M., & Radicchi, F. (2024). Robustness and resilience of complex networks. Spring Nature 6, 114-131. https://doi.org/10.1038/s42254-023-00676-y DOI: https://doi.org/10.1038/s42254-023-00676-y

Aya-Velandia, L. A. (2020). Aportes de los sistemas y redes complejas para la transformación social. Logos Ciencia & Tecnología, 12(1), 204-216. https://www.redalyc.org/journal/5177/517762281017/html/ DOI: https://doi.org/10.22335/rlct.v12i1.1066

Barabási, A. L. (2016). Network Science. [En línea]. Disponible en: http://networksciencebook. com/. Fecha de consulta: 1 de enero de 2023.

Borgatti, S. P. & Foster, P. C. (2003). The network paradigm in organizational research: A re-view and typology. Journal of Management, 29(6), 991-1013. https://doi.org/10.1016/S0149-2063(03)00087-4 DOI: https://doi.org/10.1016/S0149-2063_03_00087-4

Castaingts-Teillery, J. (2015). Campos, organizaciones, empresas y cambios estructurales. Un punto de vista a partir de la teoría de los sistemas complejos adaptativos. Análisis Organizacional, 1(7), 62-86.

Castells, M. (2009). Communication power. Oxford, New York: Oxford university press.

Chanlat, J. F. (2021). Gestión y subjetividad en el trabajo en el mundo euroamericano: tres posturas principales. Innovar, 31(79), 27-41. https://doi.org/10.15446/innovar.v31n79.91958 DOI: https://doi.org/10.15446/innovar.v31n79.91958

Chen, B., Tong, R., Chen, Y., Jiang, P., Gao, X., & Tao, H. (2023). A network key node identification method based on improved multiattribute fusion. Wireless Communications and Mobile Computing, (1), 4386621. https://doi.org/10.1155/2023/4386621 DOI: https://doi.org/10.1155/2023/4386621

Danko, L. & Crhová, Z. (2025). Rethinking the role of knowledge sharing on organizational performance in knowledge-intensive business services. Journal of the Knowledge Economy, 16(4), 13873-13893. https://doi.org/10.1007/s13132-024-02354-5 DOI: https://doi.org/10.1007/s13132-024-02354-5

Demchak, B. (2023). Cytoscape Product Roadmap. [En línea]. Disponible en: https://cytoscape. org/roadmap.html. Fecha de consulta: 1 de enero de 2023.

Espín-Noboa, L., Peixoto, T. P., & Karimi, F. (2023). Social network modeling and applications, a tutorial. arXiv preprint arXiv: 2306.11004.

Frigotto, M. L., Young, M., & Pinheiro, R. (2022). Resilience in organizations and societies: The state of the art and three organizing principles for moving forward. In R. Pinheiro, M. L. 0, & M. Young (Ed.). Towards Resilient Organizations and Societies (pp. 249-276). https://doi.org/10.1007/978-3-030-82072-5_10 DOI: https://doi.org/10.1007/978-3-030-82072-5_1

Hassel, H. & Cedergren, A. (2025). Facing the unexpected: a literature review on methods for assessing organizational adaptive capacity. Environment Systems and Decisions, 45(3), 27. DOI: https://doi.org/10.1007/s10669-025-10017-2

Hernández-Cansino, C., Carreón-Vázquez, G. y Urbiola-Solís, A. E. (2023). Una metodología a partir de los sistemas complejos adaptativos para la construcción de redes basada en procesos organizacionales. Acta Universitaria, 33, 1-18. https://doi.org/10.15174/au.2023.3804 DOI: https://doi.org/10.15174/au.2023.3804

Holland, J. H. (2004). El orden oculto: de cómo la adaptación crea la complejidad. Fondo de Cultura Económica.

Khademi, N., Bababeik, M., & Fani, A. (2021). Sparserail network robustness analysis: Functional vulnerability levels of accidents resulting from human errors. Journal of Safety Science and Resilience, 2(3), 111-123. https://doi.org/10.1016/j.jnlssr.2021.07.001 DOI: https://doi.org/10.1016/j.jnlssr.2021.07.001

Li, Z., Tang, J., Zhao, C., & Gao, F. (2023). Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks. Chaos, Solitons & Fractals, 167, 112998. https://doi.org/10.1016/j.chaos.2022.112998 DOI: https://doi.org/10.1016/j.chaos.2022.112998

Marocco, S., Marini, M., & Talamo, A. (2024). Enhancing organizational processes for service innovation: Strategic organizational counseling and organizational network analysis. Frontiers in Research Metrics and Analytics, 9, 1270501. https://doi.org/10.3389/frma.2024.1270501 DOI: https://doi.org/10.3389/frma.2024.1270501

Pandey, S. D., Ranadive, A. S., Samanta, S., & Sarkar, B. (2022). Bipolar-Valued Fuzzy Social Network and Centrality Measures. Discrete Dynamics in Nature and Society, (1), 9713575. DOI: https://doi.org/10.1155/2022/9713575

Ramos, V., Pazmiño, P., Franco-Crespo, A., Ramos-Galarza, C., & Tejera, E. (2022). Comparative organizational network analysis considering formal power-based networks and organizational hierarchies. Heliyon, 8(1). https://doi.org/10.1016/j.heliyon.2021.e08661 DOI: https://doi.org/10.1016/j.heliyon.2021.e08661

Scardoni, G. & Lau, C. (2012). Centralities based analysis of complex networks. New Frontiers in Graph Theory. https://doi.org/10.5772/35846 DOI: https://doi.org/10.5772/35846

Schwarze, A. C., Jiang, J., Wray, J., & Porter, M. A. (2024). Structural robustness and vulnerability of networks. arXiv preprint arXiv: 2409.07498. https://doi.org/10.48550/arXiv.2409.07498

Wang, M., Wang, H., & Zheng, H. (2022). A mini review of node centrality metrics in biological Networks. International Journal of Network Dynamics and Intelligence, 99-110. https://doi.org/10.53941/ijndi0101009 DOI: https://doi.org/10.53941/ijndi0101009

Watson, M. K., Winchester, C. C., Luciano, M. M., & Humphrey, S. E. (2025). Categorizing the complexity: A scoping review of structures within organizations. Journal of Management, 51(1), 309-343. https://doi.org/10.1177/01492063241271252 DOI: https://doi.org/10.1177/01492063241271252

Watts, D. J. (2003). Six degrees: The Science of a Connected Age. Random House.

Xie, Y., Desouza, K. C., & Jabbari, M. (2023). On organizational robustness: A conceptual framework. Journal of Contingencies and Crisis Management, 31(1), 105-120. https://doi. org/10.1111/1468-5973.12423 DOI: https://doi.org/10.1111/1468-5973.12423

Published

2026-08-28

How to Cite

Hernández-Cansino, C., Carreón-Vázquez, G., Urbiola-Solís, A. E., & Carrillo-González, G. (2026). Robustness and vulnerability in organizational process networks: a systemic approach for strategic management. CienciaUAT, 20(2). https://doi.org/10.29059/cienciauat.v20i2.2047

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Received 2025-08-07
Accepted 2026-08-13
Published 2026-08-28

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