The personalization–privacy paradox at the nexus of social exchange and construal level theories

Abstract

Marketing personalization requires firms to collect information that they can use to personalize their products or services, which might raise consumer privacy concerns. Prior studies on construal level theory suggest that happier Internet users would likely take future rewards in social exchanges (e.g., personalization–privacy trade‐offs) into greater consideration. Building on both social exchange and construal level theories, this article investigates the extent to which happiness with the Internet drives the personalization–privacy paradox, as well as the moderating role of experience sharing frequency as a proxy for reciprocity. An online survey administered to a representative sample of French consumers (n = 649) largely confirms the predictions. Happiness with the Internet is the strongest driver of willingness to disclose information in exchange for personalization, surpassing conventional privacy‐related constructs (e.g., trust and risk beliefs). In line with social exchange theory, reciprocity has an important influence on online social exchanges too.

Digital technologies and privacy: State of the art and research directions

“…The more recent development of the Social Exchange Theory approach to understanding the relationship between privacy and "goods" production has shown that it can successfully combine several theories. For instance, Cloarec et al (2021) add Construal Level Theory (Liberman & Trope, 1998) While such a phenomenon has been documented in other contexts (e.g., healthy vs. vice foods; Laran, 2010;Wertenbroch, 1998), it is novel in the domain of privacy.…”

“…"Consumers" decision-making process differs from hedonic and utilitarian products (Roggeveen et al, 2015), online and offline (Scarpi, 2012). Furthermore, recent works have related hedonism and utilitarianism to Construal Level Theory (Scarpi, 2021a(Scarpi, , 2021b, which has been proven to increase the explanatory power of Social Exchange Theory (Cloarec et al, 2021). Thus, hedonism and utilitarianism appear to be possible integrations to the Social Exchange Theory framework for understanding the trade-off between disclosing personal information and gaining personalization benefits.…”

“…The more recent development of the Social Exchange Theory approach to understanding the relationship between privacy and “goods” production has shown that it can successfully combine several theories. For instance, Cloarec et al (2021) add Construal Level Theory (Liberman & Trope, 1998) to the equation, providing an example of how future research could integrate Social Exchange Theory with different perspectives. Reading the privacy paradox in terms of psychological distance, Cloarec et al (2021) bring happiness into the equation.…”

“…For instance, Cloarec et al (2021) add Construal Level Theory (Liberman & Trope, 1998) to the equation, providing an example of how future research could integrate Social Exchange Theory with different perspectives. Reading the privacy paradox in terms of psychological distance, Cloarec et al (2021) bring happiness into the equation. Happiness raises individuals' construal level (Labroo & Patrick, 2009), leading individuals to apply an intertemporal discount: present costs (i.e., information disclosure) are weighted less than future gains (i.e., personalization of products and services).…”

Commodity Recommendation Model Integrating User Psychological Data Analysis

“…With the rapid development of the Internet economy, a large number of products have flooded into the e-commerce market, so that the intelligent recommendation has once again pushed to the wind ( Cloarec et al, 2022 ). Although the development of the e-commerce industry is in full swing, even so, the development of many traditional e-commerce platforms is not ideal, these traditional e-commerce platforms cannot guarantee to provide comprehensive user analysis, and mining user needs to provide the ideal recommendation program, and the lack of close contact between the user and the platform ( Cahyono et al, 2018 ; Cheng et al, 2019 ; Huang and Rust, 2021 ).…”