Data rewarding is a novel business model leading a new economic trend in mobile networks, in which the operators stimulate mobile users to watch ads with data rewards and ask for corresponding payments from advertisers. Yet, due to the uncertain nature of users’ preferences, it is always challenging for the advertiser to find the best choice of data rewards to attain an optimum balance between ad revenue and rewards spent. In this paper, we build a general contract-theoretic framework to address the problem of data rewards design in a realistic asymmetric information scenario, where each user is associated with multi-dimensional private information, i.e., data valuation, ad valuation, and ad sensitivity. In particular, we model the interplay between the advertiser and users by using a multi-dimensional contract approach, and theoretically analyze optimal data rewarding schemes. To ensure global incentive compatibility, we utilize the structural properties of our contract problem and convert the multi-dimensional contract into an equivalent one-dimensional contract. Necessary and sufficient conditions for an optimal and feasible contract are then derived to provide incentives for engagement of users in data rewarding scheme. Extensive numerical evaluations validate the efficiency of the designed multi-dimensional contract for data rewarding compared to other benchmark schemes.

中文翻译：

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移动网络数据奖励的多维契约方法

流量奖励是一种引领移动网络新经济趋势的新型商业模式，运营商通过流量奖励刺激移动用户观看广告，并要求广告主支付相应费用。然而，由于用户偏好的不确定性，广告商总是难以找到最佳的数据奖励选择，以在广告收入和奖励支出之间取得最佳平衡。在本文中，我们构建了一个通用契约理论框架来解决现实信息不对称场景中的数据奖励设计问题，其中每个用户都与多维私人信息相关联，即数据估值、广告估值和广告敏感性. 特别是，我们通过使用多维契约方法对广告商和用户之间的相互作用进行建模，并从理论上分析最优数据奖励方案。为了确保全局激励兼容性，我们利用我们合约问题的结构特性，将多维合约转换为等效的一维合约。然后推导出最优和可行合同的必要和充分条件，为用户参与数据奖励计划提供激励。与其他基准方案相比，广泛的数值评估验证了设计的多维数据奖励合同的效率。然后推导出最优和可行合同的必要和充分条件，为用户参与数据奖励计划提供激励。与其他基准方案相比，广泛的数值评估验证了设计的多维数据奖励合同的效率。然后推导出最优和可行合同的必要和充分条件，为用户参与数据奖励计划提供激励。与其他基准方案相比，广泛的数值评估验证了设计的多维数据奖励合同的效率。