Revisión de literatura: optimización del proceso de abastecimiento de una empresa

Literature review: optimization of a company's sourcing process

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En el entorno empresarial actual, la optimización del proceso de abastecimiento es esencial para la competitividad organizacional. El objetivo de este estudio fue sistematizar la evidencia científica sobre la optimización del abastecimiento en una empresa de material publicitario, mediante una revisión sistemática cualitativa siguiendo el protocolo PRISMA. La búsqueda se realizó en Scopus, SciELO, ProQuest, Clinical Key y EBSCO, para el periodo 2018-2024, empleando la ecuación: "optimization" AND "Supply optimization". Los resultados identificaron categorías relacionadas con sistemas que optimizan tiempos operativos, destacando modelos de predicción, rutas, automatización, gestión (ABC/EOQ/ERI), diseño de planta y toma de decisiones. La adopción de estos modelos exige inversión en sistemas automatizados y algoritmos que mejoran la planificación, reducen tiempos de respuesta y fortalecen la productividad e imagen corporativa. Se concluye que la integración de tecnologías emergentes, como inteligencia artificial y machine learning, genera reducciones significativas en costos y mejoras sustanciales en la eficiencia de la cadena de suministro.

In today's business environment, the optimization of the sourcing process is essential for organizational competitiveness. The objective of this study was to systematize the scientific evidence on sourcing optimization in an advertising material company, through a qualitative systematic review following the PRISMA protocol. The search was conducted in Scopus, SciELO, ProQuest, Clinical Key and EBSCO, for the period 2018-2024, using the equation: “optimization” AND “Supply optimization”. The results identified categories related to systems that optimize operating times, highlighting predictive models, routing, automation, management (ABC/EOQ/ERI), plant design and decision making. The adoption of these models requires investment in automated systems and algorithms that improve planning, reduce response times and strengthen productivity and corporate image. It is concluded that the integration of emerging technologies, such as artificial intelligence and machine learning, generates significant cost reductions and substantial improvements in supply chain efficiency.

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Ocupa Meneses, B. D. D., & Wong Cabanillas, F. J. (2025). Revisión de literatura: optimización del proceso de abastecimiento de una empresa. Impulso, Revista De Administración, 5(11), 393-407. https://doi.org/10.59659/impulso.v.5i11.151
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Artículos de Investigación

Cómo citar

Ocupa Meneses, B. D. D., & Wong Cabanillas, F. J. (2025). Revisión de literatura: optimización del proceso de abastecimiento de una empresa. Impulso, Revista De Administración, 5(11), 393-407. https://doi.org/10.59659/impulso.v.5i11.151

Referencias

Anisya, H., Basri, M. H., Adiutama, A., Widjaja, F. B., y Rachmania, I. N. (2020). Inventory level improvement in pharmacy company using probabilistic EOQ model and two echelon inventory: a case study. The Asian Journal of Technology Management, 13(3), 229-242. https://n9.cl/z9g2w

Callahany, R., y Smith, J. (2019). PNS193 Modeling adoption and optimization of automation supply chain management technology with RFID (UHF) in the us acute hospital setting. Value in Health, 22, S318. https://doi.org/10.1016/j.jval.2019.04.1550

Ciccullo, F., Pero, M., Caridi, M., Gosling, J., y Purvis, L. (2020). Integrating the environmental and social sustainability pillars into the lean and agile supply chain management paradigms. Journal of cleaner production, 172, 2336-2350. https://doi.org/10.1016/j.jclepro.2017.11.176

Contreras, F., y Olaya Guerrero, J. C. (2024). Beneficios de la implementación de la inteligencia artificial en la administración de empresas: una revisión sistemática. Impulso, Revista De Administración, 4(8), 213-228. https://doi.org/10.59659/impulso.v.4i8.58

Heidary Dahooie, J., Zamani Babgohari, A., Meidutė-Kavaliauskienė, I., y Govindan, K. (2021). Prioritising sustainable supply chain management practices by their impact on multiple interacting barriers. International Journal of Sustainable Development & World Ecology, 28(3), 267-290. https://doi.org/10.1080/13504509.2020.1795004

Ivannovich, K., Vivek, R., Richa, S., Manish, P., y Prasanna, V. (2024). Supply Chain Optimization in Industry 5.0: An Experimental Investigation Using Al. In BIO Web of Conferences (Vol. 86, p. 01093). EDP Sciences. https://doi.org/10.1051/bioconf/20248601093

Jawad, Z. N., y Balázs, V. (2024). Machine learning-driven optimization of enterprise resource planning (ERP) systems: a comprehensive review. Beni-Suef University Journal of Basic and Applied Sciences, 13(1), 4. https://doi.org/10.1186/s43088-023-00460-y

Jeong, H., Karim, R. A., Sieverding, H. L., y Stone, J. J. (2021). An application of GIS-linked biofuel supply chain optimization model for various transportation network scenarios in Northern Great Plains (NGP), USA. BioEnergy Research, 14(2), 612-622. https://doi.org/10.1007/s12155-020-10223-7

Jin, M., y Karki, S. (2024). Integrating IoT and blockchain for intelligent inventory management in supply chains: A multi-objective optimization approach for the insurance industry. Journal of Engineering Research. 16(5), 1987. https://doi.org/10.1016/j.jer.2024.04.021

Manrique, M., Teves, J., Taco, A., y Flores, J. (2019). Supply chain management: a look from the theoretical perspective. Revista Venezolana de Gerencia, Universidad del Zulia, 24(88), 1136-1146. https://www.redalyc.org/journal/290/29062051009/html/

Moreno, B., Muñoz, M., Cuellar, J., Domancic, S., y Villanueva, J. (2018). Revisiones sistemáticas: definición y nociones básicas. Revista Clínica de Periodoncia, Implantología y Rehabilitación Oral, 11(3), 184-186. https://doi.org/10.4067/S0719-01072018000300184

Narimissa, O., Kangarani-Farahani, A., y Molla-Alizadeh-Zavardehi, S. (2019). Evaluation of sustainable supply chain management performance: Dimensions and aspects. Sustainable Development, 27(4), 682-701. https://doi.org/10.1002/sd.1976

Pasupuleti, V., Thuraka, B., Kodete, C. S., y Malisetty, S. (2024). Enhancing supply chain agility and sustainability through machine learning: Optimization techniques for logistics and inventory management. Logistics, 8(3), 73. https://doi.org/10.3390/logistics8030073

Rocchio, B. J., Chipps, E., Gorsuch, P., y Wills, C. E. (2023). Automating Perioperative Inventory Management: A Quality Improvement Project. AORN journal, 117(3), 177-186. https://doi.org/10.1002/aorn.13882

Sablón-Cossío, N., Crespo, E. O., Pulido-Rojano, A., Acevedo-Urquiaga, A. J., y Ruiz Cedeño, S. D. M. (2021). Análisis de integración de la cadena de suministros en la industria textil en Ecuador. Un caso de estudio. Ingeniare. Revista chilena de ingeniería, 29(1), 94-108. http://dx.doi.org/10.4067/S0718-33052021000100094

Sirinon, J. (2024). Management of Logistics Systems to Increase the Competitiveness of a Community Enterprise Processing Herbs from Local Wisdom in Buriram Province, Thailand. Journal of Ecohumanism, 3(7), 361-371. https://www.ceeol.com/search/article-detail?id=1275617

Sirinon, P. (2024). Management of logistics systems to increase the competitiveness of a community enterprise processing herbs from local wisdom in Buriram Province, Thailand. International Journal of Logistics Management, 35(3), 567-584. https://doi.org/10.1108/IJLM-08-2023-0315

Wang, J., Zheng, R., y Wang, Z. (2022). Supply chain optimization strategy research based on deep learning algorithm. Mobile Information Systems, 2022(1), 9058490. https://doi.org/10.1155/2022/9058490

Xinfa, T., Jingjing, W., Yonghua, W., y Youwei, W. (2024). The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market. Energies, 17(18), 4691. https://doi.org/10.3390/en17184691

Yingnian, W., Hao, T., Jing, Z., Ding, W., y Hao, W. (2024). Research on optimization of supply chain inventory system under contingency conditions. RAIRO-Operations Research, 58(2), 1771-1788. https://doi.org/10.1051/ro/2024014

Zambrano-Yépez, C., Giler Kuffó , E., Vera Velásquez , M., y Franco Medranda , Y. (2020). Beneficios y desafíos del uso de las TIC en la cadena de suministro. Revista De Investigación En Tecnologías De La Información, 8(15), 128–142. https://doi.org/10.36825/RITI.08.15.012

Zhang, A., Venkatesh, V. G., Wang, J. X., Mani, V., Wan, M., y Qu, T. (2021). Drivers of industry 4.0-enabled smart waste management in supply chain operations: a circular economy perspective in china. Production Planning & Control, 34(10), 870–886. https://doi.org/10.1080/09537287.2021.1980909