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Analysis On Cost And Efficiency Of Take-out O2O Crowdsourcing Logistics And Research On Improving Schemes

Posted on:2020-09-17Degree:MasterType:Thesis
Country:ChinaCandidate:J LuoFull Text:PDF
GTID:2428330572486071Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
With rapid development of the foodservice industry is transforming to the take-out O2O(online to offline)mode,leading to difficulties in large-scale real-time terminal distribution,promoting wide practice of the crowdsourcing distribution mode based on the sharing economy theory,so as to solve the “last three kilometers” problem in logistics terminal and improve consumer experience,to realize the mode of national crowdsourcing and create values for the society.The crowdsourcing logistics with the sharing economy concept achieves rapid development.However,there are still various challenges to the O2 O crowdsourcing logistics in the starting stage;in addition,it leads to huge impacts on traditional logistics.Therefore,it is needed to analyze cost and efficiency of take-out O2 O crowdsourcing logistics and research on improving schemes,which plays important and practical roles.Firstly,this article describes the research background and significance of the outsourcing O2 O crowdsourcing as well as domestic and foreign development conditions.The article then conducts characteristic analysis on take-out O2 O crowdsourcing logistics based on literature research,and establishes mathematical models on distribution cost and distribution efficiency of merchants and social benefits.The article then gives the calculation method for mathematical model.In order to research on the order combination mechanism,after comparisons among different logistics simulation software,Flexsim software is utilized to establish the distribution cost and efficiency simulation models for O2 O crowdsourcing logistics and traditional logistics,to simulate actual distribution conditions under different modes.In addition,the article analyzes influencing factors of cost and efficiency,and proposes research on three improving schemes.In combination of merchant data of Dada,as well as the comparisons made between the mathematical model and the simulation model,the following conclusions are drawn: Not all O2 O crowdsourcing distribution cost and efficiency in all conditions are superior to the traditional distribution model.The cost and efficiency of crowdsourcing distribution of a single order are better than that of traditional distribution,and combined distribution of multiple orders can greatly reduce the distribution cost.Dynamic changes of order quantity give rise to influences on distribution cost and efficiency,and traditional merchants can improve cost and efficiency by adjusting distribution waiting strategy.According to research onimproving schemes,the quantity of crowdsourcing distributors shall be in accordance with size of order quantity;blind development of distributors will increase cost;the distance-priority order receiving scheme is superior to the same good delivery-priority order receiving scheme;the same good delivery-priority order receiving scheme is superior to the distance-priority order receiving scheme.According to research schemes,reasonable order receiving method of crowdsourcing distributors can reduce the crowdsourcing distribution cost effectively,which improves distribution efficiency.The validity of combined order distribution is determined according to related researches,which reveals in which conditions the O2 O crowdsourcing logistics have more advantages than traditional terminal logistics mode on the aspects of cost and efficiency,as well as the advantages of the same delivery position-priority order taking scheme.It provides supports for decision-making for merchants and O2 O crowdsourcing logistics platforms,and provides theoretical guidance for further development of the O2 O crowdsourcing logistics platform.
Keywords/Search Tags:take-out O2O, crowdsourcing logistics, distribution cost, distribution efficiency, improving schemes
PDF Full Text Request
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