Optimal Control Of Crowdsourcing Logistics Service Quality Based On Big Dada Technology Level

Under the Internet plus background,the emergence of crowdsourcing logistics has changed the traditional logistics mode of transportation,which can make greater use of idle resources in society,and also has the advantages of reducing logistics costs and improving distribution efficiency.However,the low access threshold of crowdsourcing logistics,the inaccurate scheduling of service platform,and the uneven distribution level of receivers lead to the low service quality,which result in the reduction of logistics demand and the low satisfaction of consumers.At the same time,crowdsourcing logistics relies on big data technology for distribution route planning and order preference analysis.Therefore,it is of great theoretical and practical significance to study the optimal control of crowdsourcing logistics service quality based on big data technology level.(1)A differential game model of crowdsourcing logistics service quality control in the case of single platform based on dynamic perspective was constructed,in which the service quality standard was introduced and reward-penalty mechanism were considered.The platform and the receiver's optimal quality control level,profits and the optimal service quality and demand track were solved by using Pontryagin maximum principle.With the comparison and numerical analysis,the results suggest that the service price is equal in the three process of crowdsourcing logistics service.After adopting the cost sharing contract,the optimal service quality,demand and total profits of centralized manners can be achieved by adjusting the cost sharing ratio,and two parties' profits can be improved compared with no cost sharing contract manners when the reward-penalty factor meets certain conditions.The higher the reward-penalty factor and commission rate,the higher the enthusiasm of the receiver to enhance quality control level and service platform's own quality control level is decreased for the purpose of cost saving.The higher the reward-penalty factor,the higher the platform's profit and the lower the receiver's profit when the service quality standard exceeds a certain value.(2)The crowdsourcing logistics service quality depends on big data technology and changes dynamically,meanwhile,crowdsourcing logistics enterprises are facing fierce competition.A quality competition differential game model of the platform and its receiver under demand competition case was constructed.The two parties' optimal quality control level,profits and the optimal service quality track under three cases were solved by using the optimal control method.The impact of big data technology on the decision-making of both sides was also discussed.The results suggest that the higher the service price,the higher the quality control level and big data technology level of the service platform.The receiver's quality control level is motivated by higher commission rate and service price.The higher price competition coefficient,the higher the profits of the service platform and the receiver.With the increase of the competitive enterprise's service price,the two parties' profits are improved when the price competition coefficient exceeds a certain value.When the initial logistics service quality is higher than a certain value,the higher service quality sensitivity coefficient,the higher the two parties' profits.The competitive platform's quality control level is not affected by the service platform's big data technology strategy,however,its own quality control level is improved.Choosing to improve the level of big data technology is more beneficial to the increase of profits of the platform and its receiver.No matter whether the platform improves the big data technology level or not,the receiver's quality control level remains unchanged.(3)In view of the surge of crowdsourcing logistics demand,crowdsourcing logistics service platform is facing the fierce competition environment of supply shortage of receivers.Considering the situation that two service platforms compete with one receiver through commission and big data technology level,a crowdsourcing logistics service quality control's differential game model based on big data technology level under supply competition case was constructed.The changes of quality control level,profits and service quality of all parties under three situations were analyzed,and the influences of choosing the strategy to improve big data technology on the service platform and the receiver were discussed.The results show that the higher the quality sensitivity coefficient,the higher the optimal quality control level of the service platforms and the receiver and the optimal big data technology level.The higher the delay cost per unit demand,the higher the service platforms' optimal quality control level.The higher the initial crowdsourcing logistics service quality,the higher the profits of service platform and receiver.The service platform adopting big data technology strategy improves the quality control level itself,but it does not affect the quality control level of the competitive platform.The platform's own profit is increased only when the proportion coefficient of big data technology cost optimization meets certain condition.As for the receiver,in the case of supply competition,the quality control level remains unchanged no matter whether the service platform adopts big data technology strategy or not.