Information Sharing as a Multidimensional, Dyadic Phenomenon: A Multilevel Study of Multiplex Relationships, Privacy, and Trust
Bryan Hammer & Andy Luse
Abstract
As a social construct, privacy is at the heart of relationships and drives the sharing of information. Previous research on privacy has taken for granted the relationship involved in information sharing. Our research theorizes that the nature of the relationship itself plays a key role in influencing privacy concerns and trust. Using network theory, we posit that privacy concerns, trust, and information sharing occur at two levels: the relational as interpersonal (i.e., dyadic) and the individual as intrapersonal. Relationships characterized as multiplex, or multidimensional, are richer and experience greater trust while reducing privacy concerns. Utilizing data collected from work groups that use digital communication platforms, we analyze our data using a covariance-based SEM multilevel model approach. Our results indicate that greater multiplex relationships lead to increases in trust, which in turn leads to greater information sharing. Multiplexity does not impact privacy concerns. Surprisingly, privacy concerns have a positive relationship with information sharing, counter to previous research. Our findings suggest that privacy mechanisms are more complex than previously modeled because they depend on the quality and type of interpersonal relationship.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.