IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v9y2025i2p59-d1643870.html
   My bibliography  Save this article

Integrated Logistics Management Through ERP System: A Case Study in an Emerging Regional Market

Author

Listed:
  • Juan Gabriel França Canon

    (Technology Axis, Campus do Sertão, Federal University of Alagoas, Delmiro Gouveia 57480-000, Brazil)

  • Robério José Rogério dos Santos

    (Technology Axis, Campus do Sertão, Federal University of Alagoas, Delmiro Gouveia 57480-000, Brazil)

  • Victor Diogho Heuer de Carvalho

    (Technology Axis, Campus do Sertão, Federal University of Alagoas, Delmiro Gouveia 57480-000, Brazil)

  • Madson Bruno da Silva Monte

    (School of Economy, Administration and Accounting, Federal University of Alagoas, Maceió 57072-900, Brazil)

  • Thiago Lima de Barros

    (Technology Axis, Campus do Sertão, Federal University of Alagoas, Delmiro Gouveia 57480-000, Brazil)

Abstract

Background : Logistics and supply chain management are crucial in modern commerce, impacting global competition, and both can directly benefit by using enterprise resource planning (ERP) systems. This case study examines key success factors behind a significant operational transformation in a company in the countryside of Alagoas, Brazil. From this context, two research questions emerge: (a) What are the main success factors that drove a significant operational transformation in logistics and supply chain management, and how did these factors impact the company’s growth? (b) How does digital transformation and adopting an ERP impact the company’s logistics activities? Methods : Data were collected through on-site observations, interviews with supervisors and a manager, and analysis of company-provided documentation. Results : The study identified key processes, stakeholders, and practices, focusing on critical success factors, mission-critical processes, and the integration of core and support functions. Notable changes were observed through key logistics performance indicators, tracking the evolution from pre-implementation to post-implementation and revealing their impact on the company’s growth. Conclusions : Improved decision making between departments significantly enhanced performance and growth. The analyzed company’s success can be attributed to a process-oriented approach, digital transformation in logistics, and investment in information technology.

Suggested Citation

  • Juan Gabriel França Canon & Robério José Rogério dos Santos & Victor Diogho Heuer de Carvalho & Madson Bruno da Silva Monte & Thiago Lima de Barros, 2025. "Integrated Logistics Management Through ERP System: A Case Study in an Emerging Regional Market," Logistics, MDPI, vol. 9(2), pages 1-25, April.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:2:p:59-:d:1643870
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/9/2/59/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/9/2/59/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lucie Sislian & Anicia Jaegler, 2022. "Linkage of blockchain to enterprise resource planning systems for improving sustainable performance," Business Strategy and the Environment, Wiley Blackwell, vol. 31(3), pages 737-750, March.
    2. Sadia Samar Ali & Rajbir Kaur, 2022. "Exploring the Impact of Technology 4.0 Driven Practice on Warehousing Performance: A Hybrid Approach," Mathematics, MDPI, vol. 10(8), pages 1-22, April.
    3. Shree Ranjan & Vijay Kumar Jha & Pralay Pal, 2016. "Literature review on ERP implementation challenges," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 21(3), pages 388-402.
    4. Carmen Isensee & Frank Teuteberg & Kai Michael Griese, 2022. "Exploring the Use of Mobile Apps for Fostering Sustainability-Oriented Corporate Culture: A Qualitative Analysis," Sustainability, MDPI, vol. 14(12), pages 1-25, June.
    5. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
    6. Zhao Tian & Vukašin Pajić & Milorad Kilibarda & Milan Andrejić, 2024. "Enhancing Distribution Efficiency Through OTIF Performance Evaluation," Mathematics, MDPI, vol. 12(21), pages 1-21, October.
    7. Mohammad Daneshvar Kakhki & Vidyaranya B. Gargeya, 2019. "Information systems for supply chain management: a systematic literature analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 5318-5339, August.
    8. Juan R. Trapero & Robert Fildes & Andrey Davydenko, 2011. "Nonlinear identification of judgmental forecasts effects at SKU level," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(5), pages 490-508, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tan Wang & L. Jeff Hong, 2023. "Large-Scale Inventory Optimization: A Recurrent Neural Networks–Inspired Simulation Approach," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 196-215, January.
    2. Geeraert, Joke & Rocha, Luis E.C. & Vandeviver, Christophe, 2024. "The impact of violent behavior on co-offender selection: Evidence of behavioral homophily," Journal of Criminal Justice, Elsevier, vol. 94(C).
    3. Léon Faure & Bastien Mollet & Wolfram Liebermeister & Jean-Loup Faulon, 2023. "A neural-mechanistic hybrid approach improving the predictive power of genome-scale metabolic models," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    4. Claudia Quinteros-Cartaya & Guillermo Solorio-Magaña & Francisco Javier Núñez-Cornú & Felipe de Jesús Escalona-Alcázar & Diana Núñez, 2023. "Microearthquakes in the Guadalajara Metropolitan Zone, Mexico: evidence from buried active faults in Tesistán Valley, Zapopan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(3), pages 2797-2818, April.
    5. Furqan Dar & Samuel R. Cohen & Diana M. Mitrea & Aaron H. Phillips & Gergely Nagy & Wellington C. Leite & Christopher B. Stanley & Jeong-Mo Choi & Richard W. Kriwacki & Rohit V. Pappu, 2024. "Biomolecular condensates form spatially inhomogeneous network fluids," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    6. Nina Tiel & Fabian Fopp & Philipp Brun & Johan Hoogen & Dirk Nikolaus Karger & Cecilia M. Casadei & Lisha Lyu & Devis Tuia & Niklaus E. Zimmermann & Thomas W. Crowther & Loïc Pellissier, 2024. "Regional uniqueness of tree species composition and response to forest loss and climate change," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    7. López Pérez, Mario & Mansilla Corona, Ricardo, 2022. "Ordinal synchronization and typical states in high-frequency digital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    8. Jessica M. Vanslambrouck & Sean B. Wilson & Ker Sin Tan & Ella Groenewegen & Rajeev Rudraraju & Jessica Neil & Kynan T. Lawlor & Sophia Mah & Michelle Scurr & Sara E. Howden & Kanta Subbarao & Melissa, 2022. "Enhanced metanephric specification to functional proximal tubule enables toxicity screening and infectious disease modelling in kidney organoids," Nature Communications, Nature, vol. 13(1), pages 1-23, December.
    9. Kiran Krishnamachari & Dylan Lu & Alexander Swift-Scott & Anuar Yeraliyev & Kayla Lee & Weitai Huang & Sim Ngak Leng & Anders Jacobsen Skanderup, 2022. "Accurate somatic variant detection using weakly supervised deep learning," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    10. Larissa Samaan & Leonie Klock & Sandra Weber & Mirjam Reidick & Leonie Ascone & Simone Kühn, 2024. "Low-Level Visual Features of Window Views Contribute to Perceived Naturalness and Mental Health Outcomes," IJERPH, MDPI, vol. 21(5), pages 1-35, May.
    11. Dennis Bontempi & Leonard Nuernberg & Suraj Pai & Deepa Krishnaswamy & Vamsi Thiriveedhi & Ahmed Hosny & Raymond H. Mak & Keyvan Farahani & Ron Kikinis & Andrey Fedorov & Hugo J. W. L. Aerts, 2024. "End-to-end reproducible AI pipelines in radiology using the cloud," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    12. Pablo García-Risueño, 2025. "Historical Simulation Systematically Underestimates the Expected Shortfall," JRFM, MDPI, vol. 18(1), pages 1-12, January.
    13. Lauren L. Porter & Allen K. Kim & Swechha Rimal & Loren L. Looger & Ananya Majumdar & Brett D. Mensh & Mary R. Starich & Marie-Paule Strub, 2022. "Many dissimilar NusG protein domains switch between α-helix and β-sheet folds," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    14. Ali Rezaei & Virág Kocsis-Jutka & Zeynep I. Gunes & Qing Zeng & Georg Kislinger & Franz Bauernschmitt & Huseyin Berkcan Isilgan & Laura R. Parisi & Tuğberk Kaya & Sören Franzenburg & Jonas Koppenbrink, 2025. "Correction of dysregulated lipid metabolism normalizes gene expression in oligodendrocytes and prolongs lifespan in female poly-GA C9orf72 mice," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    15. Oren Amsalem & Hidehiko Inagaki & Jianing Yu & Karel Svoboda & Ran Darshan, 2024. "Sub-threshold neuronal activity and the dynamical regime of cerebral cortex," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    16. Matthew Rosenblatt & Link Tejavibulya & Rongtao Jiang & Stephanie Noble & Dustin Scheinost, 2024. "Data leakage inflates prediction performance in connectome-based machine learning models," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    17. Jackie Grant & Mark Hindmarsh & Sergey E. Koposov, 2022. "The distribution of loss to future USS pensions due to the UUK cuts of April 2022," Papers 2206.06201, arXiv.org.
    18. Sayedali Shetab Boushehri & Katharina Essig & Nikolaos-Kosmas Chlis & Sylvia Herter & Marina Bacac & Fabian J. Theis & Elke Glasmacher & Carsten Marr & Fabian Schmich, 2023. "Explainable machine learning for profiling the immunological synapse and functional characterization of therapeutic antibodies," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    19. Henry Webel & Lili Niu & Annelaura Bach Nielsen & Marie Locard-Paulet & Matthias Mann & Lars Juhl Jensen & Simon Rasmussen, 2024. "Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    20. Ricardo A. Santa & Alejandro Acosta & Silvio Borrero & Annibal Scavarda, 2020. "Corporate, operational, and information systems strategies: Alignment and firm performance," Estudios Gerenciales, Universidad Icesi, vol. 36(157), pages 454-464, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlogis:v:9:y:2025:i:2:p:59-:d:1643870. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.