Achieving a Balance Between Privacy Protection and Data Collection: A Field Experimental Examination of a Theory-Driven Information Technology Solution

Businesses face a trade-off between creating stricter privacy policies for consumers and using more sophisticated data collection methods. Justice-based privacy protection describes one way to manage this trade-off. conceptualized the extent to which these characteristics affect privacy concerns and information disclosure behavior. In particular, we offered an Information Technology (IT) solution to balance the trade-off between protecting privacy and collecting consumer data. IT solution, known as Trading Privacy Policy App, Active Recommendation, which enables customer service agents to actively interact and recommend personalized privacy policies to consumers. We evaluated our solution through a field experiment involving two classic applications: a non-negotiation privacy policy application (only a non-negotiable privacy statement is published) as the base method and a privacy policy application of negotiation. , recommendation not active (only one negotiation function is integrated into the privacy policy). The results showed that the proposed negotiation, active application of the privacy policy of the recommendations lessened privacy concerns and increased consumers’ information disclosure intentions and actual disclosure behavior. A post hoc analysis confirmed these results, indicating that our design improved perceived procedural justice, interactive justice, and distributive justice among consumers and made them feel comfortable disclosing their personal information. businesses would be able to collect additional personal information from consumers, thereby contributing to a privacy-friendly environment. We discuss the contributions and implications of our proposed IT solution for consumers, businesses, developers and government officials.

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