What’s in it for me? a systematic literature review on incentive mechanisms fostering users’ data sharing behavior in data ecosystems
TL;DR
This work inductively identifies five key dimensions of incentive mechanisms and five categories of influencing factors that may shape their effectiveness and users’ data sharing behavior and proposes a conceptually grounded typology comprising eight ideal types of incentive mechanisms.
Abstract
Access to sufficient and high-quality data has become a critical driver of innovation and competitiveness in today’s data-driven economy. However, many organizations, particularly smaller companies without an established user base, struggle to build or access adequately sized datasets. Yet, often a sufficiently large data base is not available. In this context, the concept of data ecosystems gained traction. Data ecosystems describe a distinct form of digital ecosystems in which data takes the role of the central product. Data ecosystems provide a potential solution to the need for data by facilitating the access. However, these ecosystems need to maintain the sovereignty of the data-generating, private consumer. It is of utmost importance to use or distribute data only with the consumers’ consent. Therefore, motivating users to share actively data with a data ecosystem is a relevant topic. For this reason, the aim of our work is to enable a more comprehensive understanding of the subject of incentive mechanisms fostering data sharing in data ecosystems. The study employs an extended systematic literature review to aggregate prior research in this domain, developing an extensive overview on the subject and highlighting future research avenues. We inductively identify five key dimensions of incentive mechanisms and five categories of influencing factors that may shape their effectiveness and users’ data sharing behavior. Building on these insights, we propose a conceptually grounded typology comprising eight ideal types of incentive mechanisms.