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The Significant Decisions in Cold Chain Logistics

  • Sung-Ho, RYU (Graduate School of Logistics, Inha University)
  • Received : 2023.02.13
  • Accepted : 2023.03.15
  • Published : 2023.03.30

Abstract

Purpose - The prior literature has shown that there is a lack of a complete assessment of the key decisions in cold chain logistics. Such a study is required to offer recommendations for research in this expanding but under-researched topic with potentially significant management ramifications. Research design, Data, and methodology - The current researcher accumulated peer-reviewed sources from databases to augment each chosen study's validity. Selection varied between seminal works and much of the existing literature. The selection process was consistent with using a content checklist that established the inclusion and exclusion criteria. Result - The research findings indicate total five solutions regarding better decision in Cold Chain Logistics (CCL), such as (1) Pricing Decision in Cold Chain Logistics, (2) Decision on Temperature Control Decision in Cold Chain Logistics, (3) Supply Chain Network Design in Cold Chain Logistics, (4) Decision on Minimizing Inventory in Cold Chain Logistics, (5) Decision on Logistics Distribution. Conclusion - Stability of a cold chain should be maintained from manufacture or via logistical components and cold logistics products are susceptible to several variables, such as temperature, and degradation can easily harm food supply, product prices, and human health. Product safety infractions substantially impact human health, among other losses linked with a functioning CCL.

Keywords

References

  1. Bishara, R. H. (2006). Cold chain management-an essential component of the global pharmaceutical supply chain. American Pharmaceutical Review, 9(1), 105-109.
  2. Cai, X., Zhang, H., & Li, Q. (2022, April). Analysis and Design of Smart Cold Chain Logistics Simulation Model Based on Internet of Things Technology. In 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) (pp. 1352-1356). IEEE.
  3. Feng, L. (2019). Dynamic pricing, quality investment, and replenishment model for perishable items. International Transactions in Operational Research, 26(4), 1558-1575. https://doi.org/10.1111/itor.12505
  4. Han, S., & Kang, E. (2020). The marketing strategy to stimulate customer's interest in art-gallery business plan. Journal of Distribution Science, 18(8), 47-54. https://doi.org/10.15722/JDS.18.8.202008.47
  5. Haflidason, T., Olafsdottir, G., Bogason, S., & Stefansson, G. (2012). Criteria for temperature alerts in cod supply chains. International Journal of Physical Distribution & Logistics Management, 42(4), 355-371. https://doi.org/10.1108/09600031211231335
  6. Hien, D. N., & Thanh, N. V. (2022). Optimization of cold chain logistics with Fuzzy MCDM Model. Processes, 10(5), 947.
  7. Hong, J. H. (2021). A global strategy of a company that uses culture content as its core business. The Journal of Industrial Distribution & Business, 12(6), 37-46.
  8. Hosseinabadi, A. A. R., Siar, H., Shamshirband, S., Shojafar, M., & Nasir, M. H. N. M. (2015). Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises. Annals of Operations Research, 229, 451-474. https://doi.org/10.1007/s10479-014-1770-8
  9. Joshi, R., Banwet, D. K., & Shankar, R. (2009). Indian cold chain: modeling the inhibitors. British Food Journal, 111(11), 1260-1283. https://doi.org/10.1108/00070700911001077
  10. Juan, Y. (2022, September). Optimization of Multi-temperature Joint Distribution Path for Cold Chain Logistics under Carbon Emission. In 2022 7th International Conference on Power and Renewable Energy (ICPRE) (pp. 1274-1279). IEEE.
  11. Kang, E. (2020). The relationship between reinforcement of employee's customer-centric behavior and employee motivation factors. Advances in Social Sciences Research Journal, 7(7), 338-347. https://doi.org/10.14738/assrj.77.8640
  12. Kapuria, B., Talukdar, J., Muthusamy, N., & Gera, R. (2014). Designing and implementing an intelligent vaccine logistics management system for India's Universal Immunisation Programme (UIP)-'The eVIN Model'. Journal of Pharmaceutical Policy and Practice, 7(1), 1-2. https://doi.org/10.1186/2052-3211-7-1
  13. Keirstead, J., Samsatli, N., Pantaleo, A. M., & Shah, N. (2012). Evaluating biomass energy strategies for a UK eco-town with an MILP optimization model. Biomass and Bioenergy, 39, 306-316. https://doi.org/10.1016/j.biombioe.2012.01.022
  14. Kim, K., Kim, H., Kim, S. K., & Jung, J. Y. (2016). i-RM: An intelligent risk management framework for context-aware ubiquitous cold chain logistics. Expert Systems with Applications, 46(March), 463-473. https://doi.org/10.1016/j.eswa.2015.11.005
  15. Krasteva, Y., Kotzab, H., & Lienbacher, E. (2019). Analyzing logistical challenges to address food waste in the grocery retail sector. Global Business Management Review, 11(2), 97-123.
  16. Kuo, T. C., Chen, G. Y. H., Wang, M. L., & Ho, M. W. (2014). Carbon footprint inventory route planning and selection of hot spot suppliers. International Journal of Production Economics, 150(April), 125-139. https://doi.org/10.1016/j.ijpe.2013.12.005
  17. Kuswandi, B., & Nurfawaidi, A. (2017). On-package dual sensors label based on pH indicators for real-time monitoring of beef freshness. Food Control, 82, 91-100. https://doi.org/10.1016/j.foodcont.2017.06.028
  18. Lee, J. H. (2021). Effect of sports psychology on enhancing consumer purchase intention for retailers of sports shops: Literature content analysis. Journal of Distribution Science, 19(4), 5-13. https://doi.org/10.15722/JDS.19.4.202104.5
  19. Li, F., Ai, W., & Ju, T. (2022). Cold Chain Logistics Distribution Path Planning of Fresh Products in Beijing Subcenter. Sustainability, 14(17), 10622.
  20. Li, H., & Li, N. (2021, July). Research on Agricultural Product Cold Chain Logistics Management Based on Supply Chain Network Structure. In Journal of Physics: Conference Series (Vol. 1972, No. 1, p. 012082). IOP Publishing.
  21. Lutjen, M., Dittmer, P., & Veigt, M. (2013). Quality driven distribution of intelligent containers in cold chain logistics networks. Production Engineering, 7, 291-297. https://doi.org/10.1007/s11740-012-0433-3
  22. Mahmoodi, A. (2019). Joint pricing and inventory control of duopoly retailers with deteriorating items and linear demand. Computers & Industrial Engineering, 132(June), 36-46. https://doi.org/10.1016/j.cie.2019.04.017
  23. Marucheck, A., Greis, N., Mena, C., & Cai, L. (2011). Product safety and security in the global supply chain: Issues, challenges and research opportunities. Journal of operations management, 29(7-8), 707-720. https://doi.org/10.1016/j.jom.2011.06.007
  24. McDermott, H. J. (2004). Air monitoring for toxic exposures. John Wiley & Sons.
  25. Mena, C., Terry, L. A., Williams, A., & Ellram, L. (2014). Causes of waste across multi-tier supply networks: Cases in the UK food sector. International Journal of Production Economics, 152(June), 144-158. https://doi.org/10.1016/j.ijpe.2014.03.012
  26. Misni, F., Lee, L. S., & Jaini, N. I. (2021, July). Multi-objective hybrid harmony search-simulated annealing for location-inventory-routing problem in supply chain network design of reverse logistics with CO2 emission. In Journal of Physics: Conference Series (Vol. 1988, No. 1, p. 012054). IOP Publishing.
  27. Nakandala, D., Lau, H., & Zhang, J. (2016). Cost-optimization modelling for fresh food quality and transportation. Industrial Management & Data Systems, 116(3), 564-583. https://doi.org/10.1108/IMDS-04-2015-0151
  28. Nguyen, L. T., Nantharath, P., & Kang, E. (2022). The sustainable care model for an ageing population in Vietnam: Evidence from a systematic review. Sustainability, 14(5), 2518.
  29. Poonthalir, G., Nadarajan, R., & Kumar, M. S. (2020). Hierarchical Optimization of green routing for mobile advertisement vehicle. Journal of Cleaner Production, 258(10), 120661
  30. Raab, V., Petersen, B., & Kreyenschmidt, J. (2011). Temperature monitoring in meat supply chains. British Food Journal, 113(10), 1267-1289.
  31. Ringsberg, H. (2014). Perspectives on food traceability: a systematic literature review. Supply Chain Management: An International Journal, 19(5/6), 558-576. https://doi.org/10.1108/SCM-01-2014-0026
  32. Sadykov, R. (2012). Scheduling incoming and outgoing trucks at cross docking terminals to minimize the storage cost. Annals of Operations Research, 201, 423-440. https://doi.org/10.1007/s10479-012-1232-0
  33. Salleh, S. F., Gunawan, M. F., Zulkarnain, M. F. B., & Halim, A. (2019). Modelling and Optimization of biomass supply chain for bioenergy production. Journal of Environmental Treatment Techniques, 7(4), 689-695.
  34. 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.
  35. Shekarian, E. (2020). A review of factors affecting closed-loop supply chain models. Journal of Cleaner Production, 253(April), 119823.
  36. Shu, L., Qu, S., & Wu, Z. (2020). Supply chain coordination with optimal pricing and logistics service decision in online retailing. Arabian Journal for Science and Engineering, 45, 2247-2261. https://doi.org/10.1007/s13369-019-04265-z
  37. Shukla, M., & Jharkharia, S. (2013). Agri-fresh produce supply chain management: a state-of-the-art literature review. International Journal of Operations & Production Management, 33(2), 114-158. https://doi.org/10.1108/01443571311295608
  38. Sodhi, M. S., & Tang, C. S. (2021). Supply chain management for extreme conditions: research opportunities. Journal of Supply Chain Management, 57(1), 7-16. https://doi.org/10.1111/jscm.12255
  39. Sung, I. (2021). Interdisciplinary Literaure Analysis between Cosmetic Container Design and Customer Purchasing Intention. The Journal of Industrial Distribution & Business, 12(3), 21-29. https://doi.org/10.13106/JIDB.2021.VOL12.NO3.21
  40. Srivastava, S. K., Chaudhuri, A., & Srivastava, R. K. (2015). Propagation of risks and their impact on performance in fresh food retail. The International Journal of Logistics Management, 26(3), 568-602. https://doi.org/10.1108/IJLM-02-2014-0032
  41. Swanson, D., Goel, L., Francisco, K., & Stock, J. (2018). An analysis of supply chain management research by topic. Supply Chain Management: An International Journal, 12(3), 100-116. https://doi.org/10.1108/SCM-05-2017-0166
  42. Tseng, M. L., Chiu, A. S., Liu, G., & Jantaralolica, T. (2020). Circular economy enables sustainable consumption and production in a multi-level supply chain system. Resources, Conservation and Recycling, 154(March), 104601.
  43. Vali-Siar, M. M., & Roghanian, E. (2022). Sustainable, resilient and responsive mixed supply chain network design under hybrid uncertainty with considering COVID-19 pandemic disruption. Sustainable production and consumption, 30(March), 278-300. https://doi.org/10.1016/j.spc.2021.12.003
  44. Wang, G., Xia, J., & Lu, E. (2018). Design of Remote Multi-feedback System for Low-Temperature Distribution Box Based on Mobile Network Platform. In 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) (pp. 284-288). IEEE.
  45. Wang, L., Kwok, S. K., & Ip, W. H. (2010). A radio frequency identification and sensor-based system for the transportation of food. Journal of Food Engineering, 101(1), 120-129. https://doi.org/10.1016/j.jfoodeng.2010.06.020
  46. Wang, W., Zhu, A., Wei, H., & Yu, L. (2023). Optimal Preservation Effort and Carbon Emission Reduction Decision of Three-Level Cold Chain System with Low-Carbon Advertising Effect. Applied Sciences, 13(3), 1818.
  47. White III, C. C., & Cheong, T. (2012). In-transit perishable product inspection. Transportation research part e: Logistics and Transportation Review, 48(1), 310-330. https://doi.org/10.1016/j.tre.2011.08.006
  48. Woo, E. J., & Kang, E. (2020). Environmental issues as an indispensable aspect of sustainable leadership. Sustainability, 12(17), 7014.
  49. Wu, J. Y., & Hsiao, H. I. (2021). Food quality and safety risk diagnosis in the food cold chain through failure mode and effect analysis. Food Control, 120(February), 107501.
  50. Yang, Y., Zang, Y., & Qi, M. (2021, December). Robust Network Design and Last-mile Delivery in Cold Chain Logistics System. In 2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 765-772). IEEE.
  51. Zhao, L., Yu, Q., Li, M., Wang, Y., Li, G., Sun, S., ... & Liu, Y. (2022). A review of the innovative application of phase change materials to cold-chain logistics for agricultural product storage. Journal of Molecular Liquids, 365(November), 120088.
  52. Zheng, F., & Pang, Y. (2019, September). A GRASP algorithm for trailer scheduling of crossdock operations in cold-chain logistics. In 2019 International Conference on Industrial Engineering and Systems Management (IESM) (pp. 1-6). IEEE.
  53. Zheng, Z., & Huang, W. (2021, December). Research on the Location and Path Optimization of Joint Distribution of Fresh Food Cold-Chain Logistics in the Context of Big Data. In 2021 3rd International Symposium on Smart and Healthy Cities (ISHC) (pp. 99-106). IEEE.
  54. Zhu, L. (2021). The Optimization of Distribution Path of Cold Chain Logistics Based on Resource Integration. In Frontier Computing: Proceedings of FC 2020 (pp. 1385-1391). Springer Singapore.