Cold chain management is gaining plenty of attention in recent months due to the specific storage and handling requirements of the COVID19-vaccines. Similarly, food cold chain management is a highly interesting field with multiple possibilities to improve operations.
First of all, one has to note that there are multiple variants of cold chain management concepts. Varying temperature ranges exists based on product requirements ranging from ultra-cold to ambient conditions. Perishable food is predominantly either stored and transported at frozen or chilled temperature ranges.
While the desired temperature range often can be controlled during storage and transport, loading and unloading activities are more complex. Particularly, in difficult delivery settings such as hot climate or urban settings where parking spaces are sparse, the time required to unload products can results in substantial quality impacts. This does not only affect the products which are currently unloaded, but potentially all other products on board a vehicle.
As a result, planning and decision-making tools for fresh and frozen food deliveries need to consider a wide variety of influencing factors to guarantee both food safety and quality during logistics processes. In literature, a wide variety of methods exists ranging from modelling these aspects through soft or hard time windows to implementing advanced food quality models and cross-perishability effects.
A promissing research direction to further improve cold chain management is the integration of techniques from data science and analytics. Sensor data from time temperature indicators or smart labels may allow one to predict potential problems in the cold chain early. This allows decision makers to react swiftly to related events, enabling one to reduce food waste, extend shelf life and deliver products with higher quality to the customers.
Consequently, food cold chain management offers a wide range of interesting research directions and various opportunities for businesses to improve operations. If done well, food waste and energy consumption is reduced and we all can enjoy a nice cold ice cream on a hot day. If you want to learn more about this topic from different perspectives, check out the recent literature review articles listed below. Stay cool!
– Awad, M., Ndiaye, M., & Osman, A. (2020). Vehicle routing in cold food supply chain logistics: a literature review. The International Journal of Logistics Management, in press. https://doi.org/10.1108/IJLM-02-2020-0092
– Chaudhuri, A., Dukovska-Popovska, I., Subramanian, N., Chan, H. K., & Bai, R. (2018). Decision-making in cold chain logistics using data analytics: A literature review. The International Journal of Logistics Management 29(3), 839-861. https://doi.org/10.1108/IJLM-03-2017-0059
– James, S. J., James, C., & Evans, J. A. (2006). Modelling of food transportation systems–a review. International Journal of Refrigeration, 29(6), 947-957. https://doi.org/10.1016/j.ijrefrig.2006.03.017
– Shashi, S., Cerchione, R., Singh, R., Centobelli, P., & Shabani, A. (2018). Food cold chain management: : From a structured literature review to a conceptual framework and research agenda. The International Journal of Logistics Management 29(3), 792-821. https://doi.org/10.1108/IJLM-01-2017-0007
– Shashi, S., Centobelli, P., Cerchione, R. and Ertz, M. (2021). Food cold chain management: what we know and what we deserve. Supply Chain Management 26(1), 102-135. https://doi.org/10.1108/SCM-12-2019-0452
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