Research On Optimization Of Logistics Efficiency Considering Product Inventroy And Equipment Subsidy In Intelligent Logistics

In the era of "Industry 4.0" and "Internet+",the development of emerging technologies,such as blockchain,Internet of Things,and intelligent logistics equipment,such as automated guided vehicle(AGV)and new energy trucks,have promoted the rapid development of intelligent logistics.The logistics-related enterprises adopt these emerging technologies and intelligent equipment in logistics storage,transportation,and distribution,making the whole logistics system more automated and intelligent.Intelligent logistics system has not only been widely applied in practice but has also attracted extensive attention from academia.Most of the existing literature studies how to design logistics systems and optimize scheduling arrangements in distribution.Empowered by emerging technologies and intelligent equipment,logistics service providers can share product inventory and logistics information with upstream manufacturers and retailers in real-time for collaborative operational management.At this point,stakeholders’ decision-making in the intelligent logistics system will undergo fundamental changes.To improve logistics efficiency,on the one hand,logistics service providers and upstream enterprises can optimize the product inventory strategy,including product placement optimization and inventory transshipment optimization.On the other hand,they can also adopt intelligent logistics equipment in warehousing and transportation of logistics to improve picking efficiency and transportation efficiency.In this thesis,we study the inventory management of products and the subsidy policy of intelligent logistics equipment to optimize logistics efficiency in the intelligent logistics system.Firstly,to improve logistics efficiency,this thesis investigates the optimization of product placement considering the impact of cloud storage and cloud distribution logistics network.Using the logistics distribution data of large products,we build a time fixed effects panel regression model to quantify the impact of product distribution network density on logistics performance(i.e.,speed,reliability,and complexity).The result shows that increasing the proportion of products delivered from local distribution centers(i.e.,increasing the density of logistics distribution network)can shorten the delivery time,reduce the delivery complexity,and improve the on-time delivery rate.Specifically,if the proportion of products delivered from local distribution centers increases by 10%,the average delivery time can be reduced by 10%from 42 hours,the delivery complexity can be reduced by 8.3%from 1.57,and the on-time delivery rate can be further improved by 0.3%from 96.76%.Interestingly,we find that increasing the proportion of products delivered from local distribution centers has a diminishing marginal effect on the speed and complexity of logistics delivery.Therefore,considering the fixed cost of product placement in distribution centers,placing products in more distribution centers will not necessarily reduce the total cost.We establish an integer linear programming model to optimize the product placement for a product from our industrial partner.Compared the optimization results with the actual industrial performance,we find that the proportion of products delivered from local distribution centers and the percentage of the on-time delivery rate can be increased by 30.61%and 17.75%.In addition,the average delivery cost,delivery time,and delivery complexity can be decreased by 53.91%,67.22%,and 17.55%,respectively.Secondly,based on the above product placement optimization,when a product is distributed in multiple distribution centers,there will inevitably be a supply and demand mismatch between the inventory of each distribution center and the demand of its service area.At this point,preventive inventory transshipment among distribution centers is an effective tool to redistribute stock to serve consumer demand better.In addition,emerging advanced technologies enable logistics service providers(LSPs)to offer supply chain services,such as inventory management,rather than only traditional shipping services.Therefore,we study the ordering and preventive inventory transshipment problem in the LSP-led system,where a two-stage newsvendor model is built.In the traditional retailer-led system,the retailer makes the ordering and transshipment decisions.However,in the LSP-led preventive transshipment system,the LSP is the decision-maker,providing the optimal ordering and transshipment policy solution to the online retailer.An optimal two-threshold transshipment policy is proposed for the LSP-led system.As the LSP has lower transshipment operation costs than the retailer,one may expect that the LSP can bear more risk of mismatch between the transshipment and uncertain demand,leading the LSP to be more aggressive in transshipment.Interestingly,the result reveals that the transshipment quantity decided by the LSP is not necessarily higher than the retailer’s.Based on real industrial data,the evaluation result shows that preventive transshipment in the LSP-led system can bring an average increase of 40.33%in the system profit over the non-transshipment scenario.In addition,adopting the inventory transshipment policy provided by the LSP can achieve a win-win outcome for the LSP and retailer compared to the retailer-led system.Finally,in addition to improving logistics efficiency by optimizing product placement strategy and inventory transshipment policy,the adoption of intelligent logistics equipment(ILE)in warehousing and transportation can better complete product fulfillment and further improve logistics efficiency.Although ILE is green and efficient,there is heterogeneity in carriers’ belief in the ability of ILE to improve transportation capacity and in the ability of ILE to reduce environmental pollution.Some carriers distrust the effect of ILE on emission reduction and efficiency enhancement.To promote ILE,this thesis studies the optimization of intelligent logistics equipment subsidy policy.We establish a government-firm-carriers Stackelberg game wherein the government decides the subsidy policy to the ILE firm and to carriers who choose ILE,the ILE firm decides the sale price of ILE,and carriers decide to buy traditional logistics equipment or ILE.Our analysis reveals that the government should subsidize both carriers and the ILE firm when the ILE’s effectiveness is not high enough;otherwise,it is more effective to subsidize carriers but not the ILE firm.The result shows that the government subsidy can bring a win-win-win outcome for carriers,the ILE firm,and social welfare under certain conditions.Although increasing carriers’ trust in the efficiency enhancement and emission reduction value of ILE can increase their subjective willingness to adopt ILE,counterintuitively,the total profits of carriers and the profit of the ILE firm may decrease.Our results indicate that the government and the ILE firm should fully consider the heterogeneity of carriers;otherwise,the subsidy and pricing strategies not only fail to achieve the purpose of promoting ILE but may make the ILE firm "die out".Overall,the results of this research can provide some theoretical and practical guidance for the optimization of product placement and inventory transshipment,as well as the subsidy policy of intelligent logistics equipment.Moreover,the value of logistics service providers empowered by emerging technologies in the intelligent logistics system is highlighted.Some interesting theoretical research perspectives and managerial implications are provided to construct a green and efficient intelligent logistics system.