网络中的潜在代理：估计与定价

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

摘要翻译：
我们关注一个社会网络中的代理人消费一种表现出正的局部网络外部性的产品的环境。销售者可以访问关于可观察代理子集的过去消费决策/价格的数据，并可以以适当的折扣瞄准这些代理，以利用网络效应并增加其收入。该模型的一个新特点是可观察的代理与其他潜在的代理潜在地相互作用。这些潜在的代理可以从不同的渠道购买相同的产品，而不被卖方观察。可观察主体通过对潜在主体的影响直接或间接地相互影响。卖方既不知道网络中可观察部分的连接结构，也不知道网络中潜在部分的连接结构。由于网络外部性的存在，代理人的消费决策不仅取决于向其提供的价格，而且还取决于其潜在网络中邻居的消费决策（进而取决于向其提供的价格）。我们研究了卖方如何利用现有的数据来估计矩阵，该矩阵捕捉可观察的代理消费决策对提供给他们的价格的依赖关系。我们给出了一个近似稀疏条件下估计该矩阵的算法，并在高维条件下获得了估计器的收敛速度。重要的是，我们证明了这种近似稀疏性条件在文献中存在的标准条件下成立，因此我们的算法适用于一大类网络。利用估计矩阵，我们证明了在完全信息下，销售商可以构造出相对于收益最大化价格而言收益损失较小的价格，并且最优性缺口相对于网络规模消失。
---
英文标题：
《Latent Agents in Networks: Estimation and Pricing》
---
作者：
Baris Ata, Alexandre Belloni, Ozan Candogan
---
最新提交年份：
2018
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Social and Information Networks        社会和信息网络
分类描述：Covers the design, analysis, and modeling of social and information networks, including their applications for on-line information access, communication, and interaction, and their roles as datasets in the exploration of questions in these and other domains, including connections to the social and biological sciences. Analysis and modeling of such networks includes topics in ACM Subject classes F.2, G.2, G.3, H.2, and I.2; applications in computing include topics in H.3, H.4, and H.5; and applications at the interface of computing and other disciplines include topics in J.1--J.7. Papers on computer communication systems and network protocols (e.g. TCP/IP) are generally a closer fit to the Networking and Internet Architecture (cs.NI) category.
涵盖社会和信息网络的设计、分析和建模，包括它们在联机信息访问、通信和交互方面的应用，以及它们作为数据集在这些领域和其他领域的问题探索中的作用，包括与社会和生物科学的联系。这类网络的分析和建模包括ACM学科类F.2、G.2、G.3、H.2和I.2的主题；计算应用包括H.3、H.4和H.5中的主题；计算和其他学科接口的应用程序包括J.1-J.7中的主题。关于计算机通信系统和网络协议（例如TCP/IP）的论文通常更适合网络和因特网体系结构（CS.NI）类别。
--
一级分类：Computer Science        计算机科学
二级分类：Computer Vision and Pattern Recognition        计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
--
一级分类：Economics        经济学
二级分类：Theoretical Economics        理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
--
一级分类：Mathematics        数学
二级分类：Statistics Theory        统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
--
一级分类：Statistics        统计学
二级分类：Statistics Theory        统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
--

---
英文摘要：
  We focus on a setting where agents in a social network consume a product that exhibits positive local network externalities. A seller has access to data on past consumption decisions/prices for a subset of observable agents, and can target these agents with appropriate discounts to exploit network effects and increase her revenues. A novel feature of the model is that the observable agents potentially interact with additional latent agents. These latent agents can purchase the same product from a different channel, and are not observed by the seller. Observable agents influence each other both directly and indirectly through the influence they exert on the latent agents. The seller knows the connection structure of neither the observable nor the latent part of the network.   Due to the presence of network externalities, an agent's consumption decision depends not only on the price offered to her, but also on the consumption decisions of (and in turn the prices offered to) her neighbors in the underlying network. We investigate how the seller can use the available data to estimate the matrix that captures the dependence of observable agents' consumption decisions on the prices offered to them. We provide an algorithm for estimating this matrix under an approximate sparsity condition, and obtain convergence rates for the proposed estimator despite the high dimensionality that allows more agents than observations. Importantly, we then show that this approximate sparsity condition holds under standard conditions present in the literature and hence our algorithms are applicable to a large class of networks. We establish that by using the estimated matrix the seller can construct prices that lead to a small revenue loss relative to revenue-maximizing prices under complete information, and the optimality gap vanishes relative to the size of the network.
---
PDF链接：
https://arxiv.org/pdf/1808.04878

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏0 回帖

关键词：Applications Architecture Multivariate observations Contribution 卖方 价格 取决于 agents network