Carpe Data: Protecting online privacy with naive users

IF 3.2 3区 经济学 Q1 ECONOMICS Information Economics and Policy Pub Date : 2022-09-01 DOI:10.1016/j.infoecopol.2022.100988
Laura Abrardi, Carlo Cambini
{"title":"Carpe Data: Protecting online privacy with naive users","authors":"Laura Abrardi,&nbsp;Carlo Cambini","doi":"10.1016/j.infoecopol.2022.100988","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we study the optimal design of incentives to induce a digital platform to limit the extraction of data from users, whose privacy loss is further aggravated by their naive use of the platform. We show that caps on the amount of data collected can induce the optimal data-saving effort by the platform. If the platform’s effort is not observable, a menu of data caps should be provided and it entails a higher (lower) loss of privacy for less (more) naive users, relative to the first best. We also show that compensating users for their data can efficiently incentivize effort, but might increase the privacy loss of more naive users.</p></div>","PeriodicalId":47029,"journal":{"name":"Information Economics and Policy","volume":"60 ","pages":"Article 100988"},"PeriodicalIF":3.2000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Economics and Policy","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167624522000270","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper, we study the optimal design of incentives to induce a digital platform to limit the extraction of data from users, whose privacy loss is further aggravated by their naive use of the platform. We show that caps on the amount of data collected can induce the optimal data-saving effort by the platform. If the platform’s effort is not observable, a menu of data caps should be provided and it entails a higher (lower) loss of privacy for less (more) naive users, relative to the first best. We also show that compensating users for their data can efficiently incentivize effort, but might increase the privacy loss of more naive users.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Carpe Data:保护天真用户的在线隐私
在本文中,我们研究了激励的最优设计,以诱导数字平台限制用户的数据提取,用户的隐私损失进一步加剧了他们对平台的幼稚使用。我们表明,收集的数据量的上限可以诱导平台的最佳数据节省努力。如果平台的努力是不可观察的,那么应该提供一个数据上限的菜单,相对于第一种最好的方式,它需要更少(更多)天真的用户更大(更低)的隐私损失。我们还表明,对用户的数据进行补偿可以有效地激励用户的努力,但可能会增加更幼稚用户的隐私损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
5.00
自引率
10.70%
发文量
27
期刊介绍: IEP is an international journal that aims to publish peer-reviewed policy-oriented research about the production, distribution and use of information, including these subjects: the economics of the telecommunications, mass media, and other information industries, the economics of innovation and intellectual property, the role of information in economic development, and the role of information and information technology in the functioning of markets. The purpose of the journal is to provide an interdisciplinary and international forum for theoretical and empirical research that addresses the needs of other researchers, government, and professionals who are involved in the policy-making process. IEP publishes research papers, short contributions, and surveys.
期刊最新文献
Editorial Board Reaching the last mile: Digitalization of tax administration and VAT compliance at the retail stage Does mobile network coverage increase the performance of informal firms? Evidence from sub-Saharan Africa From black box to glass box: algorithmic explainability as a strategic decision The effect of lobbies' narratives on academics' perceptions of scientific publishing: A survey experiment
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1