Relative Privacy Valuations Under Varying Disclosure Characteristics

Abstract

We investigate changes to the value individuals place on the online disclosure of their private information in the presence of multiple privacy factors. We use an incentive compatible mechanism to capture individuals' willingness-to-accept (WTA) for a privacy disclosure in a series of three randomized experiments. Each experiment manipulates characteristics of a required privacy disclosure by altering the information context, intended secondary use of the disclosed private information, and the requirement to disclose personally identifying information. We collect data from two populations (college students and Amazon Mechanical Turk workers) to aid with generalizability of our results. As methodological checks to rule out lack of awareness in the participants, we first increase the saliency of the privacy disclosure characteristics in the second experiment and then require participants to watch a video on the potential consequences of disclosing private information in the third experiment. Across the three experiments, we consistently observe null effects for each of the privacy factors with the exception of two population dependent exceptions in the second study. Our participants do acknowledge the increased risk introduced by the experimental factors and the increased saliency and awareness do lead to higher privacy valuations on average. However, there is no consistent manifestation as significant main effects for the three privacy factors. This is in contrast to prior research, which has found significant effects for each of these factors when studied separately. The results provide a unique perspective on privacy valuations by demonstrating that results from prior research on simple privacy decisions may not translate to more realistic, complex privacy disclosure decisions that involve multiple factors.

Information Frictions and Heterogeneity in Valuations of Personal Data

“…To put estimates in context, we compare our baseline data valuations to a number of others in the literature in Section 3, and we compare the results across the YouGov and DDP samples. We also field an additional study to demonstrate the stated use of the respondents' data doesn't impact initial and revised valuations, consistent with Buckman et al (2019).…”

“…To ensure that our results are not sensitive to this particular stated data use, we carry out an additional robustness exercise. Buckman et al (2019) finds a null result comparing differences in valuations for personal data when the data is shared with third parties or not. To confirm this finding in our setting, we conduct a follow-up study (N=500, recruited on Amazon MTurk) where we manipulate information presented to respondents on whether we will use their Facebook data for research purposes or commercial purposes.…”

Platform Revenue Strategy Selection Considering Consumer Group Data Privacy Regulation

“…Therefore, previous studies focus on the value of user privacy information [13], motivation of disclosure [7,38], privacy disclosure, and competition in the two-sided market of the platform [35]. By contrast, we further reveal the impact of consumer data privacy disclosure level on the matching level of the platform, the consumer, and the merchants.…”

“…Most papers admit that the use of consumer private information data by the platform will have negative effects on consumers [12]. Online consumers' privacy disclosure on the platform helps the personalized recommendation system and positively affects consumers' willingness to pay [38]. However, too much information disclosed by consumers will be used to conduct business development, such as enhancing the targeted ability of advertising recommendation systems, which obviously hurts consumers to some extent.…”

The contribution of self‐disclosure to promotional response: Examining the roles of deservingness and social class

“…Personal information is considered to be a resource or a social commodity (Buckman et al, 2019; Cloarec et al, 2022; Jiang et al, 2013) insofar as it enables firms not only to provide accurate product recommendations and customized content to personalize the consumer's online experience but also to create streams of revenue by selling consumer data to information brokers (Buckman et al, 2019). Studies have shown that consumers demand monetary value in exchange for providing their personal information to firms (Buckman et al, 2019; Tomaino et al, 2022). Hence, concerning social exchange, disclosing personal information to e‐retailers to obtain services can be considered a form of resource exchange (White, 2004).…”