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Contribution Details
| Type | Conference Presentation |
| Scope | Discipline-based scholarship |
| Title | Sharing Data for Social Good: From Uninformed Consent to Misinformed Dissent |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | EMAC Conference |
| Event Type | conference |
| Event Location | Madrid (online) |
| Event Start Date | May 25 - 2021 |
| Event End Date | May 28 - 2021 |
| Abstract Text | When making the decision to use a service for personal benefits, consumers are fast to underestimate privacy-related costs and hence, freely share their personal data (uninformed consent). This cost-benefit analysis shifts, when focusing on data sharing for a social good. We show that asking people to use a service that serves a social good (containing the spread of the coronavirus), they overestimate the costs and rather not use the service due to privacy concerns (misinformed dissent). To increase data sharing for a societal cause, we test two interventions on how privacy-related information should be communicated. Our results indicate that providing additional information on a service (1) is not processed thoroughly when consumers already have a strong prior conviction about using the service; (2) increases knowledge and positive attitude only if the information is processed thoroughly; or (3) information is presented in a comparative manner compared to single information. |
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