The Role of Ecosystem Data Governance in Adoption of Data Platforms by Internet-of-Things Data Providers: Case of Dutch Horticulture Industry

Internet-of-Things (IoT) devices produce massive amounts of data, which are especially valuable when shared between businesses. However, adoption of platforms that facilitate IoT data sharing is still low. Generic literature on interorganizational systems suggests a plethora of adoption factors, but typically focuses on data sharing between pairs of organizations. In a context of ecosystems, data governance becomes important, but its relative importance as an adoption factor is yet unclear. In this article, we examine the perception of IoT data providers regarding the relative importance of ecosystem data governance as an adoption factor, in comparison with generic adoption factors. Our study is situated in the horticulture domain, where data sharing is potentially is highly valuable. We conduct a multicriteria decision-analysis survey using the best-worst method, complemented with interviews for interpreting findings. We find that businesses consider a large variety of factors equally important. Ecosystem data governance is in the middle-range, whereas factors like benefits and readiness are most important. At the same time, out of all adoption factors that platform providers can control directly, ecosystem data governance ranks among the highest. Our findings are important for informing data platform operators on what design issues to consider, in order to attract data owners.

Automated summary

This article examines the relative importance of ecosystem data governance as an adoption factor for IoT data sharing platforms. The study finds that businesses consider a variety of factors equally important, with ecosystem data governance ranking in the middle range. Factors like benefits and readiness are considered the most important. However, among the adoption factors that platform providers can control directly, ecosystem data governance ranks among the highest. These findings are important for guiding data platform operators in designing strategies to attract data owners.