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Reducing transportation greenhouse gas emissions with collaborative distribution

Author

Listed:
  • Nicolas Danloup
  • Vahid Mirzabeiki
  • Hamid Allaoui
  • Gilles Goncalves
  • Denyse Julien
  • Carlos Mena

Abstract

Purpose - – The purpose of this paper is to study the potential for improving sustainability performance in food supply networks by implementing collaborative distribution. Food supply chains generate a significant portion of CO2emissions, because of the large volume of food transportation and the large number and frequency of trips made to deliver food products to retail stores, making it available to the customers. Collaboration of partners in food supply chains will lead to reducing CO2emissions. Design/methodology/approach - – Such collaboration could be in the form of sharing trucks by retailers, to increase the fill rate of the vehicles and to reduce their empty running. A case study of the logistics network of a British company, distributing fruits and vegetables, is carried out. The company sends the products from a distribution centre to 27 retailers’ warehouses of 3 different companies in the UK. A simulation study is carried out to measure the reduced traveled distance for delivery of the products and the reduced amount of CO2emissions across two different scenarios, as a result of implementing collaborative distribution. Findings - – With this approach, the total CO2emissions are able to be reduced by at least 26 per cent. Originality/value - – The theoretical contribution of the paper is important both for showing the role of simulation and collaborative distribution for developing the green supply chain solutions management and their indicating to the applications to logistics and product delivery.

Suggested Citation

  • Nicolas Danloup & Vahid Mirzabeiki & Hamid Allaoui & Gilles Goncalves & Denyse Julien & Carlos Mena, 2015. "Reducing transportation greenhouse gas emissions with collaborative distribution," Management Research Review, Emerald Group Publishing Limited, vol. 38(10), pages 1049-1067, October.
    • Handle: RePEc:eme:mrrpps:v:38:y:2015:i:10:p:1049-1067
    DOI: 10.1108/MRR-11-2014-0262
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    Citations

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    Cited by:

    1. Rocio de la Torre & Canan G. Corlu & Javier Faulin & Bhakti S. Onggo & Angel A. Juan, 2021. "Simulation, Optimization, and Machine Learning in Sustainable Transportation Systems: Models and Applications," Sustainability, MDPI, vol. 13(3), pages 1-21, February.
    2. Snežana Tadić & Mladen Krstić & Milovan Kovač, 2023. "Assessment of city logistics initiative categories sustainability: case of Belgrade," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1383-1419, February.
    3. Thomas Hacardiaux & Jean-Sébastien Tancrez, 2020. "Assessing the environmental benefits of horizontal cooperation using a location-inventory model," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(4), pages 1363-1387, December.
    4. Lagorio, Alexandra & Pinto, Roberto, 2021. "Food and grocery retail logistics issues: A systematic literature review," Research in Transportation Economics, Elsevier, vol. 87(C).
    5. Waltho, Cynthia & Elhedhli, Samir & Gzara, Fatma, 2019. "Green supply chain network design: A review focused on policy adoption and emission quantification," International Journal of Production Economics, Elsevier, vol. 208(C), pages 305-318.
    6. Thomas Hacardiaux & Christof Defryn & Jean-Sébastien Tancrez & Lotte Verdonck, 2022. "Balancing partner preferences for logistics costs and carbon footprint in a horizontal cooperation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 121-153, March.

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