IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v314y2022i2d10.1007_s10479-019-03455-0.html
   My bibliography  Save this article

A simulation model to investigate impacts of facilitating quality data within organic fresh food supply chains

Author

Listed:
  • Magdalena Leithner

    (University of Natural Resources and Life Sciences, Vienna)

  • Christian Fikar

    (University of Natural Resources and Life Sciences, Vienna
    WU Vienna University of Economics and Business)

Abstract

Demand for and production of organic fresh food play an increasing role worldwide. As a result, a growing amount of fresh fruits and vegetables has to be transported from predominantly rural production regions to customers mostly located in urban ones. Specific handling and storage conditions need to be respected along the entire supply chain to maintain high quality and product value. To support organic food logistics operations, this work investigates benefits of facilitating real-time product data along delivery and storage processes. By the development of a simulation-based decision support system, sustainable deliveries of organic food from farms to retail stores are investigated. Generic keeping quality models are integrated to observe impacts of varying storage temperatures on food quality and losses over time. Computational experiments study a regional supply chain of organic strawberries in Lower Austria and Vienna. Results indicate that the consideration of shelf life data in supply chain decisions allow one to reduce food losses and further enables shifting surplus inventory to alternative distribution channels.

Suggested Citation

  • Magdalena Leithner & Christian Fikar, 2022. "A simulation model to investigate impacts of facilitating quality data within organic fresh food supply chains," Annals of Operations Research, Springer, vol. 314(2), pages 529-550, July.
    • Handle: RePEc:spr:annopr:v:314:y:2022:i:2:d:10.1007_s10479-019-03455-0
    DOI: 10.1007/s10479-019-03455-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-019-03455-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-019-03455-0?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. A J Higgins & C J Miller & A A Archer & T Ton & C S Fletcher & R R J McAllister, 2010. "Challenges of operations research practice in agricultural value chains," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(6), pages 964-973, June.
    2. Tijskens, L. M. M. & Polderdijk, J. J., 1996. "A generic model for keeping quality of vegetable produce during storage and distribution," Agricultural Systems, Elsevier, vol. 51(4), pages 431-452, August.
    3. Grunow, Martin & Piramuthu, Selwyn, 2013. "RFID in highly perishable food supply chains – Remaining shelf life to supplant expiry date?," International Journal of Production Economics, Elsevier, vol. 146(2), pages 717-727.
    4. Dong Li & Xiaojun Wang, 2017. "Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5127-5141, September.
    5. Soto-Silva, Wladimir E. & Nadal-Roig, Esteve & González-Araya, Marcela C. & Pla-Aragones, Lluis M., 2016. "Operational research models applied to the fresh fruit supply chain," European Journal of Operational Research, Elsevier, vol. 251(2), pages 345-355.
    6. de Keizer, Marlies & Akkerman, Renzo & Grunow, Martin & Bloemhof, Jacqueline M. & Haijema, Rene & van der Vorst, Jack G.A.J., 2017. "Logistics network design for perishable products with heterogeneous quality decay," European Journal of Operational Research, Elsevier, vol. 262(2), pages 535-549.
    7. Haijema, René & Minner, Stefan, 2016. "Stock-level dependent ordering of perishables: A comparison of hybrid base-stock and constant order policies," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 215-225.
    8. Rong, Aiying & Akkerman, Renzo & Grunow, Martin, 2011. "An optimization approach for managing fresh food quality throughout the supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 421-429, May.
    9. Ahumada, Omar & Villalobos, J. Rene, 2009. "Application of planning models in the agri-food supply chain: A review," European Journal of Operational Research, Elsevier, vol. 196(1), pages 1-20, July.
    10. Borodin, Valeria & Bourtembourg, Jean & Hnaien, Faicel & Labadie, Nacima, 2016. "Handling uncertainty in agricultural supply chain management: A state of the art," European Journal of Operational Research, Elsevier, vol. 254(2), pages 348-359.
    11. Magdalena Leithner & Christian Fikar, 2018. "Simulating Fresh Food Supply Chains by Integrating Product Quality," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 671-676, Springer.
    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. Lejarza, Fernando & Pistikopoulos, Ioannis & Baldea, Michael, 2021. "A scalable real-time solution strategy for supply chain management of fresh produce: A Mexico-to-United States cross border study," International Journal of Production Economics, Elsevier, vol. 240(C).
    2. Jianli Luo & Chen Ji & Chunxiao Qiu & Fu Jia, 2018. "Agri-Food Supply Chain Management: Bibliometric and Content Analyses," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    3. Behzadi, Golnar & O’Sullivan, Michael Justin & Olsen, Tava Lennon & Zhang, Abraham, 2018. "Agribusiness supply chain risk management: A review of quantitative decision models," Omega, Elsevier, vol. 79(C), pages 21-42.
    4. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.
    5. Soto-Silva, Wladimir E. & Nadal-Roig, Esteve & González-Araya, Marcela C. & Pla-Aragones, Lluis M., 2016. "Operational research models applied to the fresh fruit supply chain," European Journal of Operational Research, Elsevier, vol. 251(2), pages 345-355.
    6. Rana Azab & Rana S. Mahmoud & Rahma Elbehery & Mohamed Gheith, 2023. "A Bi-Objective Mixed-Integer Linear Programming Model for a Sustainable Agro-Food Supply Chain with Product Perishability and Environmental Considerations," Logistics, MDPI, vol. 7(3), pages 1-29, July.
    7. Jonkman, Jochem & Barbosa-Póvoa, Ana P. & Bloemhof, Jacqueline M., 2019. "Integrating harvesting decisions in the design of agro-food supply chains," European Journal of Operational Research, Elsevier, vol. 276(1), pages 247-258.
    8. Yu, Min & Nagurney, Anna, 2013. "Competitive food supply chain networks with application to fresh produce," European Journal of Operational Research, Elsevier, vol. 224(2), pages 273-282.
    9. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun & Hafsa Saeed, 2023. "Optimal pricing in the presence of IoT investment and quality-dependent demand," Annals of Operations Research, Springer, vol. 324(1), pages 869-892, May.
    10. Fuchigami, Helio Yochihiro & Tuni, Andrea & Barbosa, Luísa Queiroz & Severino, Maico Roris & Rentizelas, Athanasios, 2021. "Supporting Brazilian smallholder farmers decision making in supplying institutional markets," European Journal of Operational Research, Elsevier, vol. 295(1), pages 321-335.
    11. Juan Carlos Pérez-Mesa & Laura Piedra-Muñoz & Mª Carmen García-Barranco & Cynthia Giagnocavo, 2019. "Response of Fresh Food Suppliers to Sustainable Supply Chain Management of Large European Retailers," Sustainability, MDPI, vol. 11(14), pages 1-24, July.
    12. Javier Arturo Orjuela-Castro & Juan Pablo Orejuela-Cabrera & Wilson Adarme-Jaimes, 2022. "Multi-objective model for perishable food logistics networks design considering availability and access," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1244-1270, December.
    13. de Keizer, Marlies & Akkerman, Renzo & Grunow, Martin & Bloemhof, Jacqueline M. & Haijema, Rene & van der Vorst, Jack G.A.J., 2017. "Logistics network design for perishable products with heterogeneous quality decay," European Journal of Operational Research, Elsevier, vol. 262(2), pages 535-549.
    14. Tuğçe Taşkıner & Bilge Bilgen, 2021. "Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review," Logistics, MDPI, vol. 5(3), pages 1-27, August.
    15. Andrea Gallo & Riccardo Accorsi & Giulia Baruffaldi & Riccardo Manzini, 2017. "Designing Sustainable Cold Chains for Long-Range Food Distribution: Energy-Effective Corridors on the Silk Road Belt," Sustainability, MDPI, vol. 9(11), pages 1-20, November.
    16. Víctor M. Albornoz & Gabriel E. Zamora, 2021. "Decomposition-based heuristic for the zoning and crop planning problem with adjacency constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 248-265, April.
    17. Volha Yakavenka & Ioannis Mallidis & Dimitrios Vlachos & Eleftherios Iakovou & Zafeiriou Eleni, 2020. "Development of a multi-objective model for the design of sustainable supply chains: the case of perishable food products," Annals of Operations Research, Springer, vol. 294(1), pages 593-621, November.
    18. Ahumada, Omar & Villalobos, J. Rene, 2011. "Operational model for planning the harvest and distribution of perishable agricultural products," International Journal of Production Economics, Elsevier, vol. 133(2), pages 677-687, October.
    19. Gaukler, Gary M. & Zuidwijk, Rob A. & Ketzenberg, Michael E., 2023. "The value of time and temperature history information for the distribution of perishables," European Journal of Operational Research, Elsevier, vol. 310(2), pages 627-639.
    20. Na Luo & Tava Lennon Olsen & Yanping Liu, 2021. "A Conceptual Framework to Analyze Food Loss and Waste within Food Supply Chains: An Operations Management Perspective," Sustainability, MDPI, vol. 13(2), pages 1-21, January.

    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:spr:annopr:v:314:y:2022:i:2:d:10.1007_s10479-019-03455-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.