Research On Pricing Strategy Of Parcel Crowdshipping Under Fixed Task Situation

It is a common practice in the existing express transportation and distribution activities to focus on multi-period delivery requirements in a large-scale manner,and to achieve the delivery of goods through transshipment and distribution.However,under this model,it is difficult for companies to achieve rapid response to customers at a low cost.How to solve the contradiction between transportation timeliness and economy has become a difficult point in the operation of express companies.Crowdsourcing is considered to be one of the most promising solutions.It integrates passenger and freight transportation and uses private car resources on the road to help shippers complete their transportation tasks.The types of transportation crowdsourcing currently studied are mostly random,that is,transportation tasks are randomly presented at time points.However,express shipments transshipped through express delivery sites often have the characteristics of a fixed delivery period and no additional shipments during the delivery period.Such fixed task scenarios are more common in supermarket distribution activities with automatic sorting equipment.In the process of express transportation crowdsourcing in a fixed task context,pricing is the guarantee for the development of crowdsourcing activities.If the price is too low,the shipper may not be able to attract a suitable number of carriers;if the price is too high,it may cause the shipper to be out of stock during the entrusted period.Both of these phenomena will cause the shipper's actual transportation cost to be higher than the optimal transportation cost.In view of this,from the perspective of economy and timeliness,this article proposes a crowdsourcing model of express transportation between transit yards and border outlets using public transportation resources;the goal is to maximize the costsaving expectations of the shipper,and the construction based on potential carriers.The shipper's revenue management model of choice behavior,and the key issues such as the structural characteristics of the potential carrier's choice behavior model,the forecasting method of visits,and the model algorithm are studied.The main research work of this paper is as follows:(1)A new idea of pricing using revenue management theory in the field of transportation crowdsourcing is proposed.Based on the current research status of transportation crowdsourcing and pricing at home and abroad,the research scope of transportation crowdsourcing pricing under the fixed task situation is defined,the functional characteristics of express delivery network are clarified,the spatial location and business relationship between express transit yards and outlets are analyzed,the express crowdsourcing network that includes mass transportation resources is constructed.At the same time,it deeply analyzes the relationship between supply,demand and pricing of both parties in the express transportation crowdsourcing network,explores the feasibility of revenue management applied to express transportation crowdsourcing,and designs the overall process of transportation task crowdsourcing pricing under fixed task scenarios.(2)The selection behavior model of crowdsourcing potential carriers was established.Carrier selection behavior analysis is an important part of transportation crowdsourcing revenue management and the basis for constructing a dynamic pricing model.Considering the task attributes and task utility that affect potential carriers,a crowd-sourcing potential carrier selection behavior model is established,and the structural characteristics of the model are analyzed,and the relationship between the parameters to be estimated is explored.In actual operation,there are various types of tasks classified according to the attributes of transportation tasks.The selection of the carrier is not only affected by price factors,but may also be affected by other attributes of the task.The paper changes the previous method of determining the probability of a potential carrier's task by only using the task price factor,and takes into account the carrier's preference for task attributes,and establishes a potential carrier selection behavior model with multi-task attributes compatible with the dynamic pricing model.(3)Aiming at the situation where the number of visiting carriers can be observed,a dynamic pricing model based on the number of visits by potential carriers is constructed.In the process of express transportation crowdsourcing,affected by weather changes and other factors,it is difficult to accurately predict the actual visit rate of potential carriers during the entrusted period.If the pricing process is based on the potential carrier's visit rate and the real visit.The rate deviation is large,which will bring risks to operations.Combining the real-time visit volume data of potential carriers during the task entrustment period,the paper uses negative binomial distribution to propose a real-time method to predict the visit volume of potential carriers in the future.Combined with the potential carrier's selection behavior of express transportation tasks,construct the shipper cost-saving expectation maximization model proposes a variable rate dynamic pricing strategy with one person,one order and one person with multiple orders,and the algorithm for solving the model is given.(4)Aiming at the scenario where only observable tasks are carried,a dynamic pricing model based on express consignment data is constructed.In the process of task entrustment,the operator may observe and record all the potential carriers who visited,or may not observe the visits of potential carriers who have not carried the task,and can only check the time when the express was entrusted and the entrusted price.In response to this situation,a real-time prediction method of potential carrier visits based on negative binomial distribution and potential carrier selection behavior model is proposed;according to the revenue management theory,the model is constructed with the goal of maximizing the shipper's cost saving expectations.A variable rate dynamic pricing strategy was introduced.Finally,through the analysis of examples,the effects of the two proposed variable-rate dynamic pricing strategies and fixed-rate pricing strategies are compared.The main innovations of the thesis are: a new idea of using transportation crowdsourcing and revenue management theory to solve the problem of express delivery at border points in the express network;establish a multi-task attribute of potential carrier selection behavior model,and propose a real-time prediction method for the number of visits by potential carriers and express entrusted data;the establishment of a shipper's cost-saving expectation maximization model is transformed into a variable dynamic dynamic pricing strategy of one person,one order and one person for multiple orders.