An incentive mechanism based on endowment effect facing social welfare in Crowdsensing

Abstract

Mobile CrowdSensing(MCS) is a new type of network which needs a large number of users to collect data to complete the sensing task and requires users to have a high level of participation. In the current research, the incentive purpose is mainly achieved by paying certain rewards to service providers. However, due to the demand for data quality and quantity, platforms often have high consumption. Most of the current studies assume that the evaluation of an item by a node is not affected by its ownership status. But behavioral economics points out that because of the existence of endowment effect, the evaluation of the value of an item by a node is greater when it is owned than when it is not owned, thereby affecting the value evaluation strategy of the node. Therefore, inspired by the phenomenon that enterprises use share dividends to stimulate endowment effect of employees in daily life and thus motivate employees to maintain loyalty, the paper constructs a mapping relationship between it and MCS and designs a Reverse Combinatorial Auction Based Endowment Effect (RCBEE) incentive mechanism. The paper designs endowment assets and assigns them to selected nodes according to the relationship between multiple coefficients of nodes, so as to introduce the endowment effect. The paper analyzes the change of the node on the evaluation value of endowment assets, changes the node income, and reconstructs the income matrix. On the one hand, the RCBEE mechanism continuously strengthens the node’s endowment intensity by setting the holding period; on the other hand, it introduces the contribution threshold to trigger the node’s endowment effect, so that users can maximize the incentive goal of social welfare by reducing the bid price or completing more tasks. Simulation experiments show that, compared with the traditional incentive mechanism, RCBEE reduces the payment cost and increases the social welfare.