An Informational Theory of Privacy

Jann, Ole; Schottmüller, Christoph

doi:10.2139/ssrn.2853468

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…In light of recent technological developments which have made tracking and information dissemination increasingly cheap, the conformity arising from the desire to maintain social image may potentially have further consequences. Aggregate behavior becomes less informative about individuals' true preferences, which creates a problem for information aggregation (Jann and Schottmüller, 2016) and motivating new research into the optimal level of privacy in a fast-changing society (Ali and Bénabou, 2016).…”

Section: Discussionmentioning

confidence: 99%

Curating social image: Experimental evidence on the value of actions and selfies

Holm

Samahita

2018

Journal of Economic Behavior & Organization

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We manipulate the information subjects can share on the web concerning socially sensitive actions (public good contribution) and visibility (selfie) to determine the effect on social image, as captured by the price subjects demand for publication. The overall conclusion from the experiment is that theory about social reputation can predict subjects' social-signaling behavior. People take costly decisions to "filter" information about themselves (in retrospect) before it is published. We also report results of a more exploratory nature and find that taking a selfie has a strong negative impact on cooperation among frequent selfie takers, but not on other subjects.

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Section: Discussionmentioning

confidence: 99%

Curating social image: Experimental evidence on the value of actions and selfies

Holm

Samahita

2018

Journal of Economic Behavior & Organization

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“…Daughety and Reinganum (2010) explore the tradeoffs between incentives provided by visibility and the conformism this induces on agent behavior, which leads to possible over-investment in the public good. Jann and Schottmüller (2016) show that reduced privacy leads to impaired information aggregation. However, none of these studies address the potential loss of control from esteem-based sanctions, or the optimal joint level of the two incentives.…”

Section: Reputation Incentives In the Economics Literaturementioning

confidence: 99%

On esteem-based incentives

Mazyaki

Weele

2019

International Review of Law and Economics

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The rise of the internet, increased connectivity and higher availability of personal data increases the relevance of incentives based on reputation and the allocation of esteem. However, their use is controversial: critics argue that shaming can lead to a loss of control over the size of the sanction and to mob justice. We use the signaling model of social behavior by Bénabou and Tirole (2011) to explore the effect of esteembased incentives and their interaction with traditional fines. We show that the use of esteem and stigma can indeed lead to a loss of control by generating multiple equilibria, some of which feature high levels of compliance and high levels of stigma. Moreover, the deterrent effect of monetary and esteem incentives is interdependent. If both types of incentives are costly to implement, esteem incentives should optimally be used relatively more for rare behaviors and in societies that have more heterogeneous values.

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“…Other work has explored how the mechanisms for extracting user information and possession of information itself a ect the design of targeted/personalized pricing (e.g.,Candogan et al 2012, Bloch and Quérou 2013, Fainmesser and Galeotti 2016, 2020, Elliott et al 2021, Montes et al 2018, Ichihashi 2020b, Valletti and Wu 2020, selective selling, service systems(Hu et al 2020); what is the impact on social image visibility(Ali and Bénabou 2020), advertising strategies(Galeotti and Goyal 2009, Shen and Miguel Villas-Boas 2017, Bimpikis et al 2016, the extent of competition (Casadesus-Masanell and Hervas-Drane 2015) and mergers of digital businesses(Prat and Valletti 2019), overall consumer behavior(Goldfarb and Tucker 2011, Koh et al 2015, Jann and Schottmüller 2020, Gradwohl 2017). 27 Jullien et al 2020 considers a digital business that sells data services to third-parties who may be good or bad for users.…”

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confidence: 99%

Digital Privacy

2023

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We study the incentives of a digital business to collect and protect users’ data. The users’ data the business collects improve the service it provides to consumers, but they may also be accessed, at a cost, by strategic third parties in a way that harms users, imposing endogenous users’ privacy costs. We characterize how the revenue model of the business shapes its optimal data strategy: collection and protection of users’ data. A business with a more data-driven revenue model will collect more users’ data and provide more data protection than a similar business that is more usage driven. Consequently, if users have small direct benefit from data collection, then more usage-driven businesses generate larger consumer surplus than their more data-driven counterparts (the reverse holds if users have large direct benefit from data collection). Relative to the socially desired data strategy, the business may over- or undercollect users’ data and may over- or underprotect it. Restoring efficiency requires a two-pronged regulatory policy, covering both data collection and data protection; one such policy combines a minimal data protection requirement with a tax proportional to the amount of collected data. We finally show that existing regulation in the United States, which focuses only on data protection, may even harm consumer surplus and overall welfare. This paper was accepted by Itai Ashlagi, revenue management and market analytics.

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An Informational Theory of Privacy

Cited by 4 publications

References 15 publications

Curating social image: Experimental evidence on the value of actions and selfies

Curating social image: Experimental evidence on the value of actions and selfies

On esteem-based incentives

Digital Privacy

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