IDEAS home Printed from https://ideas.repec.org/a/vrs/ecoman/v14y2022i1p26-37n4.html
   My bibliography  Save this article

Order picking and loading-dock arrival punctuality performance indicators for supply chain management: A case study

Author

Listed:
  • Marzialia Micaela

    (Engineering Department, Universidad Nacional del Sur (UNS), Argentina)

  • Rossit Daniel Alejandro

    (Engineering Department, Universidad Nacional del Sur (UNS), Argentina, INMABB, CONICET-UNS, Argentina)

  • Toncovicha Adrián

    (Engineering Department, Universidad Nacional del Sur (UNS), Argentina)

Abstract

Supply chain activity control is an essential part of Supply Chain Management (SCM), ensuring compliance with customer requirements. This paper presents a case study into the control of SCM activities. The study analysed two areas involving two different SC links associated with order picking, and outsourced truck freights, respectively. The studied company had problems with these links. An approach based on developing a KPI (Key Performance Indicator) was proposed to address the issues. Consequently, different affected processes were analysed and characterised, considering the relevant data for defining a KPI. Then, strategies and methods were devised for data collection and processing regarding the system’s current state. Finally, tools were designed to facilitate the interpretation of the system’s current state and thus, pave the way for the decision-making process on corrective measures.

Suggested Citation

  • Marzialia Micaela & Rossit Daniel Alejandro & Toncovicha Adrián, 2022. "Order picking and loading-dock arrival punctuality performance indicators for supply chain management: A case study," Engineering Management in Production and Services, Sciendo, vol. 14(1), pages 26-37, March.
  • Handle: RePEc:vrs:ecoman:v:14:y:2022:i:1:p:26-37:n:4
    DOI: 10.2478/emj-2022-0003
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/emj-2022-0003
    Download Restriction: no

    File URL: https://libkey.io/10.2478/emj-2022-0003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lohman, Clemens & Fortuin, Leonard & Wouters, Marc, 2004. "Designing a performance measurement system: A case study," European Journal of Operational Research, Elsevier, vol. 156(2), pages 267-286, July.
    2. Dmitry Ivanov, 2018. "Structural Dynamics and Resilience in Supply Chain Risk Management," International Series in Operations Research and Management Science, Springer, number 978-3-319-69305-7, December.
    3. Maestrini, Vieri & Luzzini, Davide & Maccarrone, Paolo & Caniato, Federico, 2017. "Supply chain performance measurement systems: A systematic review and research agenda," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 299-315.
    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. Lima-Junior, Francisco Rodrigues & Carpinetti, Luiz Cesar Ribeiro, 2019. "Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks," International Journal of Production Economics, Elsevier, vol. 212(C), pages 19-38.
    2. Rafał Haffer, 2018. "Supply Chain Performance Measurement System Of Logistics Service Providers. A Conceptual Framework And Research Agenda," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 18, pages 85-108.
    3. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    4. Maciej Urbaniak & Piotr Rogala & Piotr Kafel, 2023. "Expectations of manufacturing companies regarding future priorities of improvement actions taken by their suppliers," Operations Management Research, Springer, vol. 16(1), pages 296-310, March.
    5. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 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, Elsevier, vol. 160(C).
    6. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    7. Surajit Bag & Muhammad Sabbir Rahman, 2024. "Navigating circular economy: Unleashing the potential of political and supply chain analytics skills among top supply chain executives for environmental orientation, regenerative supply chain practice," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 504-528, February.
    8. Marta Negri & Alessandra Neri & Enrico Cagno & Gabriele Monfardini, 2021. "Circular Economy Performance Measurement in Manufacturing Firms: A Systematic Literature Review with Insights for Small and Medium Enterprises and New Adopters," Sustainability, MDPI, vol. 13(16), pages 1-27, August.
    9. Dennis Vegter & Jos van Hillegersberg & Matthias Olthaar, 2021. "Performance Measurement Systems for Circular Supply Chain Management: Current State of Development," Sustainability, MDPI, vol. 13(21), pages 1-18, November.
    10. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    11. Maestrini, Vieri & Luzzini, Davide & Caniato, Federico & Ronchi, Stefano, 2018. "Effects of monitoring and incentives on supplier performance: An agency theory perspective," International Journal of Production Economics, Elsevier, vol. 203(C), pages 322-332.
    12. Maria Ghufran & Khurram Iqbal Ahmad Khan & Fahim Ullah & Wesam Salah Alaloul & Muhammad Ali Musarat, 2022. "Key Enablers of Resilient and Sustainable Construction Supply Chains: A Systems Thinking Approach," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    13. Jamshed Raza & Yuxin Liu & Jianwei Zhang & Nan Zhu & Zohaib Hassan & Habib Gul & Sikander Hussain, 2021. "Sustainable Supply Management Practices and Sustainability Performance: The Dynamic Capability Perspective," SAGE Open, , vol. 11(1), pages 21582440211, March.
    14. Nakandala, Dilupa & Samaranayake, Premaratne & Lau, H.C.W., 2013. "A fuzzy-based decision support model for monitoring on-time delivery performance: A textile industry case study," European Journal of Operational Research, Elsevier, vol. 225(3), pages 507-517.
    15. César Martínez-Olvera & Jaime Mora-Vargas, 2019. "A Comprehensive Framework for the Analysis of Industry 4.0 Value Domains," Sustainability, MDPI, vol. 11(10), pages 1-21, May.
    16. Jääskeläinen, Aki, 2021. "The relational outcomes of performance management in buyer-supplier relationships," International Journal of Production Economics, Elsevier, vol. 232(C).
    17. Maria Persdotter Isaksson & Hana Hulthén & Helena Forslund, 2019. "Environmentally Sustainable Logistics Performance Management Process Integration between Buyers and 3PLs," Sustainability, MDPI, vol. 11(11), pages 1-19, May.
    18. El Baz, Jamal & Ruel, Salomée, 2021. "Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era," International Journal of Production Economics, Elsevier, vol. 233(C).
    19. El-Awady Attia & Ali Alarjani & Md. Sharif Uddin & Ahmed Farouk Kineber, 2023. "Determining the Stationary Enablers of Resilient and Sustainable Supply Chains," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    20. Li, Guo & Xue, Jing & Li, Na & Ivanov, Dmitry, 2022. "Blockchain-supported business model design, supply chain resilience, and firm performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).

    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:vrs:ecoman:v:14:y:2022:i:1:p:26-37:n:4. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.