Analytics and Data-Driven Methods and Practices in Platform Ecosystems: a systematic literature review

The emergence of platform ecosystems has transformed the business landscape in many industries, giving rise to novel modes of interorganizational cooperation and value co-creation, as well as unconventional challenges. The vast traces of data generated by platform ecosystems makes them ripe for the use of analytics and data-driven methods aimed at improving their health, performance, business outcomes, and evolution. However, the research on the application of analytics within platform ecosystems is limited and spread across multiple disciplines. To address this gap, we conducted a systematic literature review on the application of analytics and data-driven methods and practices within platform ecosystems. A total of 56 studies were reviewed, and underwent data extraction, analysis, and synthesis processes. In addition to presenting themes and patterns in the recent and relevant literature on platform ecosystems analytics, our review offers the following outcomes: an actionable overview of the analytics toolbox currently used within platform ecosystems—spanning domains such as machine learning, deep learning, data science, modelling, simulation, among others—; a roadmap for practitioners to achieve analytics maturity; and a summary of underexplored research areas.