The purpose of this paper is to optimize a two-level perishable product supply chain by increasing its revenue with the Internet of Things (IoT). It particularly investigates how radio-frequency identification (RFID) technology impacts the revenue of the supply chain.
In this paper, two revenue models were built to calculate the revenue of perishable product supply chain before and after the application of IoT to analyze the influences of IoT on perishable product supply chain. In the case study, particular data of an aquatic product supply chain were analyzed through these models which were later solved by a computer simulation method based on Colonial Competitive Algorithm, a new heuristic algorithm inspired by imperialistic competition in human society.
Using these revenue models to compare the revenues of supply chain before and after the application of IoT, this paper concludes that the application of IoT can efficiently optimize a perishable product supply chain by balancing its wholesale profits and its total costs including logistics costs, therefore, increasing its overall revenue. However, this conclusion is only applicable for large enterprises, while small enterprises are not supposed to introduce IoT due to its high cost.
The revenue models built in this paper can be used to evaluate the profits of supply chain and help enterprises determine how to maximize their profits and whether they should introduce IoT in a perishable product supply chain. In addition, through the analysis of case study, this paper gives several valuable suggestions to help enterprises reduce their logistics costs and increase their overall revenue.
Yan, R. (2017), "Optimization approach for increasing revenue of perishable product supply chain with the Internet of Things", Industrial Management & Data Systems, Vol. 117 No. 4, pp. 729-741. https://doi.org/10.1108/IMDS-07-2016-0297
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