Abstract:

In recent years， with the rapid development of platform economy， on-demand service platforms such as instant grocery delivery， meal delivery and ride-hailing have gradually become a part of daily life. The agents of these platforms may be part-time or full-time， they have the autonomy of service effort， and it is private information， the platform cannot directly observe the degree of the agent's effort. And， with the change of market environment， the operation and market position of platform enterprises are not static， but more dynamic and continuous， and the incentive contract of the platform to the agent is not invariable， but constantly changing under the influence of many external factors. In this paper， for the dynamic incentive contract problem of on-demand platform with both part-time and full-time agents under asymmetric information， considering the participation constraints and incentive compatibility constraints of agents， taking the change of platform service goodwill as the state variable， the dynamic incentive contract models of platform employing part-time， full-time and simultaneous agents are constructed respectively by using principal-agent theory， the optimal control method is used to solve the equilibrium strategy of platform and agent under different situations， the effects of service cost， information asymmetry， platform service goodwill and other related parameters are revealed， and the optimal decisions under different principal-agent models are compared and analyzed. The results suggest that： （1） When the service cost coefficient and risk sensitivity coefficient of a certain type of agent increase， the service effort level of this type of agent in different situations will decrease， and the platform enterprise should reduce the incentive intensity to it， but the platform does not need to change the incentive intensity to another type of agent. （2） When the initial service goodwill of the platform is low， the optimal trajectory of the guarantee money and incentive contract charged by the platform to the part-time agent will first monotonically increase and then stabilize with the passage of time， while the fixed reward and the corresponding incentive contract provided by the platform to the full-time agent will monotonically decrease and then stabilize with the passage of time； However， when the initial service goodwill of the platform is high， the optimal trajectory of the variables related to part-time and full-time agents in the early stage is just opposite to that when the initial service goodwill is low. （3） When the platform changes from employing part-time or full-time agents to employing both types of agents at the same time， the service effort level of the agents will decrease， and the incentive intensity of the platform should be increased， but the guarantee money charged by the platform to the part-time agents and the fixed remuneration provided to the full-time agents should be strategically optimized and adjusted according to the service provider's sensitivity to the platform’s incentive contract. In addition， the optimal service effort of the platform under the three principal-agent modes are different. （4） Finally， the numerical simulation shows that the platform is the most advantageous in the mode of entrusting part-time agents， while the profitability is the weakest in the mode of full-time agents， but it is the second best in the mode of entrusting two types of agents at the same time. The results provide good insights for on-demand platforms in the design of incentive contracts.

Key words: sharing economy, dynamic incentive contract, part-time and full-time agents, optimal control theory, principal-agent model