Análisis bibliométrico de la gestión de la cadena de suministro en la nube: datos empíricos y seguridad

doi:10.5281/zenodo.20941511

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Publicado: 2026-08-01

DOI: https://doi.org/10.5281/zenodo.20941511

Palabras clave:

Cloud supply chain management, scientific production, cybersecurity, empirical data.

Rafael Emiliano Apolinario Quintana

Universidad de Guayaquil, Ecuador.

https://orcid.org/0000-0003-1719-5425

Humberto Pedro Segarra Jaime

Universidad de Guayaquil, Ecuador.

https://orcid.org/0000-0003-3946-952X

Monica Annabelle Caicedo Leones

Universidad de Guayaquil, Ecuador.

https://orcid.org/0000-0002-1986-2992

Delia Alexandra Cevallos Castro

Universidad de Guayaquil, Ecuador.

https://orcid.org/0000-0002-9515-0196

Wilsom Ruben Molina Chagerben

Universidad de Guayaquil, Ecuador.

https://orcid.org/0009-0002-3284-901X

Resumen

This research analyzes the phenomenon of the increasing interest on cloud supply chain management (CSCM) through bibliometric analysis. We wanted to know about how the empirical data can show how to defend the supply systems from a third part attack. The methodology employed is descriptive, based on the analysis of bibliometric data obtained from the Web of Science database. (WoS). The sample includes 1,715 records of scientific publications between 2013 and 2024, analyzed using VoSviewer software to visualize bibliometric networks. They indicate a sustained growth in scientific production on CSCM, with peaks in 2019 and 2022. The most relevant journals include IFAC Papersonline and Sustainability. China leads in scientific production, followed by the USA and India. The institutions with the highest number of publications are South China University of Technology and Hong Kong Polytechnic University. This review showed that potential danger related of its use is not easy to solve, and although, there is a general optimistic context to receive this kind of technology, empirical data in analyzed literature does not support yet the cybersecurity issues.

Número

Núm. 27 (mayo-agosto) (2026): Resistencia epistémica ante el avance tecnológico-científico. Preservar la humanidad ante lo artificial.

Sección

Investigación

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.

Cómo citar

Bibliometric analysis of cloud supply chain management: empirical data and security. (2026). Encuentros. Revista De Ciencias Humanas, Teoría Social Y Pensamiento Crítico., 27 (mayo-agosto), 505-521. https://doi.org/10.5281/zenodo.20941511

Referencias

Aji, F. (2024). Role Of Supply Chain Management In The Production System Company And Operations. Dinamik, 29(2), 109-115.

Alvarez, D. (2021). Análisis del abandono universitario en España: un estudio bibliométrico. Universidad Nueva Granada, 51(2), 241-261.

Apolinario, R., & Guevara, D. (2021). El efecto mediador de la capacidad ejecutiva para la innovación entre la gestión del conocimiento y el rendimiento de la cadena de suministros. Información tecnológica, , 1-14.

Ardito, L., Messeni, A., Panniello, U., & Achille, G. (2019). Towards Industry 4.0: Mapping digital technologies for supply chain management-marketing integration. Business Process Management Journal, 25(2), 323-346.

Asad, A. (2023). Cloud-Based Supply Chain Management: Optimizing Logistics and Operations. Department of Computer science, University of California , 1-8.

Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805.

Bibby, L., & Dehe, B. (2018). Defining and assessing industry 4.0 maturity levels – case of the defence sector. Production Planning & Control, 29(12), 1030-1043.

Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157-177.

Cai, W., & Huang, Z. (2O14). The Structural Design of the Logistics Service Supply Chain, Based On Cloud Logistics. Proceeding of 2013 International Symposium on Applied Engineering, Technical, and Innovation, 148-153.

Cai, Y., Guan, K., Peng, J., Wang, S., Seifert, C., Wardlow, B., & Li, Z. (2018). A high- performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach. Remote Sensing of Environment, 210, 35-47.

Castillo, A., & Casterron, M. (2010). Investigación en Comunicación. Estudio bibliométrico de las Revistas de Comunicación en España. Comunicación y Sociedad, 23(2)., 289-327.

Castro Aniyar, D. (2014). Más acá de la razón. Utopía Y Praxis Latinoamericana, 4(7). https://produccioncientificaluz.org/index.php/utopia/article/view/18284

Dwivedi, Y., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., & Crick, T. (2021).

Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57.

Ferreira, F., Pinheiro, G., Machado, M., & Pastana, I. (2024). Producción Científica sobre la Salud Mental de las Personas Transexuales en la Base de datos de Scopus: Estudio Bibliometrico. Cogitare enfermagen, 29, 1-13.

Frank, A., Santos, L., & Ayala, N. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15-26.

Hu, H., Wen, Y., Chua, T.-S., & Li, X. (2014). Toward Scalable Systems for Big Data Analytics: A Technology Tutorial. IEEE Access (2), 652-687.

Ivanov, D., Dolgui, A., & Sokolov, B. (2022). Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”. Transportation Research Part E: Logistics and Transportation Review, 160.

Karumanchi, M., Sheeba, J., Pradeep, S., & Kodavali, L. (2023). An Improved Integrity- Based Hybrid Multi-User Data Access Control for Cloud Heterogeneous Supply Chain Databases. International Journal on Recent and Innovation Trends in Computing and Communication, 1-10.

Kava, J., & Chinmayie, K. (2023). Cloud Computing a key to Supply Chain Management: Embracing the Cloud Advantage. International Journal For Multidisciplinary Research, 1-7.

Kong, Y., Zhang, M., & Ye, D. (2017). A belief propagation-based method for task allocation in open and dynamic cloud environments. Knowledge-Based Systems, 115, 123-132.

Korpela, K., Hallikas, J., & Dahlberg, T. (2017). Digital Supply Chain Transformation toward Blockchain Integration. Conference on System Sciences, 10.

Kshetri, N. (2017). Blockchain's roles in strengthening cybersecurity and protecting privacy. Telecommunications Policy, 41(10), 1027-1038.

Kusiak, A. (2018). Smart manufacturing. International Journal of Production Research, 56(1-2), 508-517.

Lacković, Z., Dvorski, S., & Ivana., D. (2017). A literature review on the Application of the Cloud Technology in Supply Chains. Central European Conference on Information and Intelligent Systems - Conference Proceedings., 135-144.

Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431-440.

Li, S., Sun, Q., & Liu, S. (2021). Risk assessment for supply chain based on Cloud model.

Journal of Intelligent & Fuzzy Systems, 3523-3540.

López, E. (2022). Estudio bibliométrico sobre mitos y verdades de la lactancia materna.

Npunto, V(50), 136-154.

López, Y., Cruz, N., Avila, J., & Borlinic, M. (2023). Bibliometric study about hotel competitiveness in Scopus and Web of Science. Revista interamericana de ambiente y turismo, 19(2), 1-17.

Manzano, O., Peñaranda, M., & Luna, J. (2021). Sostenibilidad y proyectos sostenibles: Estudio bibliométrico. Revista Cientifica Profundida, 1-15.

Naveen, M., Reddy, D., Buyya, R., Venugopal, K., Iyengar, S., & Patnaik, L. (2024). Secure pharmaceutical supply chain using blockchain in IoT cloud systems, 26. Internet of Things, 1-28.

Ooi, K.-B., Lee, V.-H., Tan, G. W.-H., Hew, T.-S., & Hew, J.-J. (2018). Cloud computing in manufacturing: The next industrial revolution in Malaysia? Expert Systems with Applications, 93, 376-394.

Ovalle, L., Moreno, Z., Olivares, M., & Silva, H. (2018). Habilidades y capacidades del emprendimiento: un estudio bibliométrico. Revista Venezolana de Gerencia , 217- 234.

Oztemel, E., & Gursev, S. (2020). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31, 127-182.

Reddy, P., Pham, Q.-V., B, P., Deppa, N., Dev, K., Reddy, T., . . . Liyanage, M. (2022).

Industry 5.0: A survey on enabling technologies and potential applications. Journal of Industrial Information Integration, 26.

Sengupta, J., Ruj, S., & Das Bit, S. (2020). A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT. Journal of Network and Computer Applications, 149.

Sharma, R., Kamble, S., Gunasekaran, A., Kumar, V., & Kumar, A. (2020). A systematic literature review on machine learning applications for sustainable agriculture supply chain performance. Computers & Operations Research, 119.

Tan, Y., Gu, L., Xu, D., & Li, M. (2024). Supply Chain Inventory Management from the Perspective of “Cloud Supply Chain"-A Data Driven Approach. Mathematics 12(4), 573-581. doi: 10.3390/math12040573.

Tzounis, A., Katsoulas, N., Bartzanas, T., & Kittas, C. (2017). Internet of Things in agriculture, recent advances and future challenges. Biosystems Engineering. 164, 31-48.

Valencia, A., Montoya, I., & Montoya, A. (2016). Intención emprendedora en estudiantes universitarios: Un Estudio Bibliométrico. Intagible Capital, 12 (4), 881-992.

Verma, R. (2024). Supply Chain Management: Optimizing Efficiency and Sustainability in the Supply Network. Journal of Advanced Management Studies, 1(2), 13-18.

Wang, C., Bi, Z., & Xu, L. (2014). IoT and Cloud Computing in Automation of Assembly Modeling Systems. IEEE Transactions on Industrial Informatics, 10(2), 1426-1434.

Wang, F., Guo, J., & Zhan, Q. (2016). Supply Chain Quality Management System Reaseach Based on Cloud Technology. 016 International Conference on Management Science and Engineering (ICMSE 2016), 33-40.

Wolfert, S., Ge, L., Verdouw, C., & Bogaardt. (2017). Big Data in Smart Farming – A review. Agricultural Systems, 153, 69-80.

Wu, D., Rosen, D., Wang, L., & Scharfer, D. (2015). Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation. Computer-Aided Design, 59, 1.14.

Xu, B., Xu, L. D., Cai, H., Xie, C., Hu, J., & Bu, F. (2014). Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services. IEEE Transactions on Industrial Informatics, 10(2), 1578-1586.

Yang, J. (2019). Construction and Optimization of Port Logistics Service Supply Chain Based on Cloud Computing. Jornal od Cosastal Research, 80-83.

Zhang, H.-X. (2014). Research on Role of Cloud Computing in Optimization of Supply Chain Management. Proceeding of the 2014 International Conference on Economic Management and Trade Cooperation, 130-135.

Zhang, Y., Niu, Z., Liu, C., Liu, C., & Hou, K. (2024). System Dynamics Analysis for Impact of Cloud-Based Information-Sharing on Supply Chain Performance.

International Journal of Industrial Engineering-Theory Applications and Practice, 31(2), 234-257.

Zhong, R., Xu, X., Klots, E., & Newman, S. (2017). Intelligent Manufacturing in the Context of Industry 4.0: A Review. Engineering, 3(5), 616-630.