Data-Driven Health Monitoring of Platform Ecosystems: A Systematic Literature Review
Paper in proceeding, 2025
Platform ecosystems have transformed value creation across industries by enabling large-scale co-creation through networks of interconnected actors interacting via a shared technological core. While this structure accelerates innovation and growth, it also introduces governance challenges due to the multi-sided nature and conflicting goals of participating stakeholders. This complexity necessitates unconventional performance evaluation metrics and health monitoring approaches capable of delivering data-driven insights into the impact of platform design and governance decisions. Meanwhile, the vast volumes of data produced by platform and software ecosystems present an opportunity to achieve real-time data-driven monitoring of the health and performance of such socio-technical systems. Despite this potential, no prior secondary research has consolidated knowledge on data-driven evaluation of platform ecosystems health and performance. To fill this gap, we conducted a systematic literature review of 52 primary studies retained after appraisal. Our analysis identified 416 distinct health indicators on four hierarchical levels across three main health categories. Descriptive, thematic, and cross-analysis of the extracted data, in addition to reviewing the retrieved reports of the selected studies, enabled the following contributions: a thematic synthesis of the existing body of literature on the topic; a six-step five-phase maturity roadmap for data-driven ecosystem health monitoring; practical guidance for platform orchestrators; and a research agenda emphasizing underexplored research areas and suggested future research directions.
decision making
platform ecosystems
data analytics
performance evaluation
system monitoring