Small Profits and Quick Returns: An Incentive Mechanism Design for Crowdsourcing Under Continuous Platform Competition

Abstract

Crowdsourcing can be applied to the Internet-of-Things (IoT) systems to provide more scalable and efficient services to support various tasks. As the driving force of crowdsourcing is the interaction among participants, various incentive mechanisms have been proposed to attract and retain a sufficient number of participants to provide a sustainable crowdsourcing service. However, there exist some gaps between the modeled entities or markets in the existing works and those in reality: 1) dichotomous task valuation and workers' punctuality, and 2) crowdsourcing service market monopolized by a platform. To bridge those gaps of such impractical assumption, we model workers' heterogeneous punctuality behavior and task depreciation over time. Based on those models, we propose an Expected Social Welfare Maximizing (ESWM) mechanism that aims to maximize the expected social welfare by attracting and retaining more participants in the long-term, i.e., multiple rounds of crowdsourcing. In the evaluation, we modeled the continuous competition between the ESWM and one of the existing works in both short-term and long-term scenarios. Simulation results show that the ESWM mechanism achieves higher expected social welfare and platform utility than the benchmark by attracting and retaining more participants. Moreover, we prove that the ESWM mechanism achieves the desirable economic properties: individual rationality, budget-balance, computational efficiency, and truthfulness.

Blockchain Enabled Credible Energy Trading at the Edge of the Internet of Things

“…Additionally, the majority of existing research has concentrated on developing offline bilateral auction mechanisms and supporting a single type of task and fixed auction service models. Accordingly, the literature [15] proposes an expected social welfare maximized mechanism (ESWM), which aims to enhance expected social welfare by attracting and retaining more participants over a long time. The literature [16] takes into account an actual crowdsourcing application with an on-demand service strategy.…”

“…According to [15], the time-varying function of the ECS's task valuation is proposed with the degree of urgency of energy consumption:…”

“…According to [15], consider the problem of whether the IoTD can provide the energy required by the edge server within a specified time, modeling this stochastic behavior as a probability density function, using the following truncated normal distribution:…”

“…However, when the IoTD provides the promised energy during the time period beyond the specified peak, the task valuation is zero in the binary task model, but in the model proposed in this paper, it is still possible to provide energy to the ECS without this time period, but with a devaluation. Considering the stochastic nature of the energy provided by the IoTD, combined with [15], an expected social welfare (ESW) is used to judge the excellence of the crowdsourcing service, defined as follows:…”

Customer‐oriented sales modeling strategy in a big data environment

“…If the demands increase more than the price falls and it will lead to increase in total revenue. "Small profits and quick returns" is a strategy to increase sales volume by reducing the profit of unit goods so that it help shopping center obtain more benefits, see References 4‐7. Yaxin Ma and Shaohua Yang investigated the factors of affecting female e‐shopper's satisfaction with cosmetic products.…”