Combining surveys and digital trace data can enhance the analytic potential of both data types. We present two studies on factors influencing data sharing behavior for different types of digital trace data: Facebook, Twitter, Spotify, and health app data. Across those data types, we compare the relative impact of five factors on data sharing: data type, data sharing method, respondent characteristics, sample composition, and incentives. The results show large differences between the data types and sharing methods, especially related to task difficulty and respondent burden. Higher incentives generally increase data sharing rates, whereas the influence of respondent characteristics depends on the respective data types.

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As our modern world has become increasingly digitalized, various types of data from different data domains are available that can enrich survey data. To link survey data to other sources, consent from the survey respondents is required. This article compares consent to data linkage requests for seven data domains: administrative data, smartphone usage data, bank data, biomarkers, Facebook data, health insurance data, and sensor data. We experimentally explore three factors of interest to survey designers seeking to maximize consent rates: consent question order, consent question wording, and incentives. The results of the study using a German online sample (n = 3,374) show that survey respondents have a relatively high probability of consent to share smartphone usage data, Facebook data, and biomarkers, while they are least likely to share their bank data in a survey. Of the three experimental factors, only the consent question order affected consent rates significantly. Additionally, the study investigated the interactions between the three experimental manipulations and the seven data domains, of which only the interaction between the data domains and the consent question order showed a consistent significant effect.

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