Valuing Intrinsic and Instrumental Preferences for Privacy

Lin, Tesary

doi:10.2139/ssrn.3406412

Cited by 18 publications

(22 citation statements)

References 67 publications

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“…Putting these values in the context of the prior literature, and we see our estimates significantly exceed many existing studies (Benndorf and Normann, 2018;Lin, 2020). Existing work has focused on less sensitive data and less data quantity, so the nature of the data we are asking about and the amount of data lead to valuations that are roughly an order of magnitude higher.…”

Section: Baseline Valuationsmentioning

confidence: 62%

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Economic Value of Data: Quantification Using Online Experiments

Collis¹,

Moehring²,

Sen³

2021

AEA Randomized Controlled Trials

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We conduct incentive compatible choice experiments to measure the economic value of social media data. We focus on the value that users place on their personal data related to the three biggest social media platforms: Facebook, Instagram and Twitter. We find that the median Willingness to Accept (WTA) of users for the entire "stock" of data for Facebook and Instagram is $300 each which is 20% higher than Twitter valued at $250. We use data valuations from a recent data breach settlement by Facebook to provide information interventions. We find that reducing these information frictions about the value of data can make users revise their valuations upwards. They do not

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Section: Baseline Valuationsmentioning

confidence: 62%

“…Acquisti et al (2013) analyze preferences of individuals to keep their transactions in a store anonymous. Lin (2020) analyzes the WTA of individuals for different demographic variables with household income and information on children being the variables with the highest WTA while gender has the lowest WTA.…”

Section: Introductionmentioning

confidence: 99%

Economic Value of Data: Quantification Using Online Experiments

Collis¹,

Moehring²,

Sen³

2021

AEA Randomized Controlled Trials

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“…Information Externalities: An important consequence of a consumer's privacy decision is the informational externality generated by that decision, as information revealed by one consumer can be used to predict the behavior of another consumer. 8,9 Several recent theoretical studies argue how such externalities can lead to the underpricing of data, and results in socially excessive data collection (Fair eld and Engel, 2015;Choi, Jeon and Kim, 2019;Acemoglu et al, 2019;Bergemann, Bona i and Gan, 2019;Liang and Madsen, 2019). Braghieri (2019) theoretically studies how privacy choices by consumers can have pecuniary externalities on other consumers by a ecting rms' incentives for price discrimination.…”

Section: Consequences Of Data Privacy Regulationmentioning

confidence: 99%

The Economic Consequences of Data Privacy Regulation: Empirical Evidence from GDPR

2020

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Utilizing a novel dataset from an online travel intermediary, we study the effects of EU's General Data Protection Regulation (GDPR). The opt-in requirement of GDPR resulted in 12.5% drop in the intermediary-observed consumers, but the remaining consumers are trackable for a longer period of time. These findings are consistent with privacy-conscious consumers substituting away from less efficient privacy protection (e.g, cookie deletion) to explicit opt out-a process that would make opt-in consumers more predictable. Consistent with this hypothesis, the average value of the remaining consumers to advertisers has increased, offsetting some of the losses from consumer opt-outs.

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“…For example, excessive customer data collection may reduce the credibility of firm communications (Gardete & Bart, 2018). However, if customers recognize economic benefits, for example, from a competitor that offers a product similar to the one marketed by the focal firm but for a lower price, they may react more favorably (Lin, 2019).…”

Section: Signals and Trust In The Relationshipmentioning

confidence: 99%

How consumer digital signals are reshaping the customer journey

Schweidel

Bart

Inman

et al. 2022

J. of the Acad. Mark. Sci.

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Marketers are adopting increasingly sophisticated ways to engage with customers throughout their journeys. We extend prior perspectives on the customer journey by introducing the role of digital signals that consumers emit throughout their activities. We argue that the ability to detect and act on consumer digital signals is a source of competitive advantage for firms. Technology enables firms to collect, interpret, and act on these signals to better manage the customer journey. While some consumers’ desire for privacy can restrict the opportunities technology provides marketers, other consumers’ desire for personalization can encourage the use of technology to inform marketing efforts. We posit that this difference in consumers’ willingness to emit observable signals may hinge on the strength of their relationship with the firm. We next discuss factors that may shift consumer preferences and consequently affect the technology-enabled opportunities available to firms. We conclude with a research agenda that focuses on consumers, firms, and regulators.

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Valuing Intrinsic and Instrumental Preferences for Privacy

Cited by 18 publications

References 67 publications

Economic Value of Data: Quantification Using Online Experiments

Economic Value of Data: Quantification Using Online Experiments

The Economic Consequences of Data Privacy Regulation: Empirical Evidence from GDPR

How consumer digital signals are reshaping the customer journey

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