This project closely examines data aggregation to understand what types of aggregation are normatively and descriptively important to individuals and how do different types and degree of aggregation impact individual trust. This proposed research would advance knowledge and understanding within the study of big data, trust, and business ethics. Initial investigations into data aggregation have been technical to ensure accuracy and diminish unwanted bias. This research explores the conceptually important types of aggregation - information type, time, location, context, technology - which are normatively important for users. This project also extends the work around the ethical implications of big data by focusing on normative judgments of data aggregation. The studies will provide empirical evidence to support policy decisions around aggregating, storing, and deleting consumer data. The results will be disseminated broadly to enhance scientific and technological knowledge through conferences across disciplines in business, ethics, and privacy. Big data relies upon aggregating data from heterogeneous sources to create new knowledge and identify novel trends: researchers look for patterns in social networking sites, marketers understand consumer demands by aggregating behavior over contexts online, a website can track consumer interests over devices. Attention thus far has focused on technical capabilities of aggregating data over time and space through matching records, de(re)-identification, and the potential use of the data. This research will fill in a gap in the literature by collecting empirical data to understand individuals' behavioral responses towards different types and degrees of data aggregation practices by different data practitioners. This project aims to focus first on inductively exploring the important types of aggregation - across technology/devices, across time, across location, across contexts, across information types - through factorial vignette survey methodology. This exploratory phase aims to identify the most important factors in judging data aggregation as reinforcing trust. The second phase will measure the impact of these important types of data aggregation on individual trust through experiments.
ETHICS OF DATA AGGREGATION: PRIVACY, TRUST, AND FAIRNESS