Research On Matching And Incentive Strategy Of “A” Freight Transport Sharing Platform Considering User Behaviors

In recent years,with the rapid development of “Internet +”,many traditional industries have undergone changes,and the logistics industry has also made innovations in the model with the help of technologies such as cloud computing and mobile internet.Especially in the field of road freight transportation,a large number of freight transportation sharing platforms have entered the market,and it is expected to solve the problem of asymmetric information and high cost of traditional road freight transportation through the agglomeration effect of the platform.In face of the fierce market competition,a lot of platforms compete for users with a large amount of subsidies.However,the key to the sustainable development of the freight transportation sharing platform is that they can match the suppliers and demanders quickly improve the efficiency of freight transportation,bring value to both suppliers and demanders,and take some measures to ensure that the platform has enough users to achieve profitability,which is also the focus of the platform in operation.Based on the summary and analysis of a large number of literature,this paper analyses the problems of freight transportation sharing platform under the background of platform “A”,mainly including the following three points: Firstly,the preciseness of the matching between suppliers and demanders needs to be further improved.Now with the help of information technology,the freight transportation sharing platform can recommend suitable matching objects for users,but after inputting relevant conditions on the platform,the number of matching objects for users is large and the quality is not high.Secondly,the impact of the psychological factors of both users is ignored in the matching of suppliers and demanders.When the freight transportation sharing platform breaks the limitation of time and space to bring convenience to people,it also increases the uncertainty of the transaction on the platform.In the face of uncertain environment,both suppliers and demanders show the behavior of loss aversion,which will have a certain impact on the matching decision of the platform.Thirdly,faced with the competition and the influence of various uncertainties,users do not necessarily accept the matching results after the platform completes the matching.What measures should the platform take to encourage users to accept the matching results of the platform and complete the transaction on the platform,so as to effectively control the user’s choice behavior to achieve maximum profit is also a major problem in the process of platform operation.In view of the above problems,the first part of this paper studies the matching between suppliers and demanders of freight transportation sharing platform “A”.Firstly,taking into account the different concerns of both sides,the satisfaction evaluation index system are constructed.Then,in the process of satisfaction calculation,the Cumulative Prospect Theory(CPT)is used to introduce the users’ attitude of loss aversion.Based on this,a two-sided matching model taking maximizing user satisfaction and matching pairs as the optimal goals is build,in which the constraint of time windows is considered.Because of the influence of various uncertainties,after the matching between suppliers and demanders is completed,whether the users accept the matching results of the platform depends on their utility or benefit which is measured by satisfaction of the matching and other factors.So,based on the matching results of the first part and considering competition,fees,the satisfaction of matching results,the waiting cost of users and other factors,the second part of this paper establishes incentive model to study the optimal incentive strategy of platform “A”,which aims at maximizing short-term profits and long-term profits of platform “A”.The research shows that after considering the loss aversion behavior of both sides in the two-sided matching,the satisfaction of the suppliers and demanders is obviously improved;and there is no invalid matching when taking into account the constraint of time windows,although the satisfaction has a certain degree of decline;at last,maximizing the matching pairs between demanders and suppliers can avoid some vehicles being neglected.Secondly,when the platform adopts incentive measures,in the short term,the profit of the platform is improved,and the optimal incentive strategy is negatively correlated with the waiting cost of competitive platform 2,and positively correlated with the ratio of service level of platform 2 and platform “A”.In the long-term,the initial profit of the platform is lower than that of the non-incentive state,but with the effect of incentives,the proportion of suppliers and demanders accepting matching results increases rapidly,and the profit of the platform also increases rapidly exceeding that of the non-incentive state.Moreover,the optimal incentive strategy gradually decreases with time,when the proportion of users accepting matching results reaches a certain level,the platform will no longer incentive,but the profit is still higher than that of the non-incentive state.Above results show that the research on the matching and incentive strategy of the freight transportation sharing platform is helpful to improve the correctness and efficiency of supply-demand matching and the profit of the platform.