Identifying future avenues of research for platform ecosystems. A topic modeling analysis

In this study, we employ topic modeling to systematically explore the platform ecosystem literature and identify emerging trends and potential avenues for future research. By leveraging computational techniques, we uncover hidden thematic structures and patterns in text data, providing valuable insights into the current state of research and pointing towards promising directions for future investigation. Our analysis draws from a comprehensive dataset of academic articles and conference proceedings, revealing key themes and trends in the platform ecosystem discourse. We examine the evolving research landscape and synthesize the key findings into coherent topic clusters, illustrating the breadth and depth of the platform ecosystem literature. Our analysis highlights the interdisciplinary nature of the field, encompassing various research domains such as business models, governance, value co-creation, entrepreneurship, among others. Additionally, we identify significant research gaps and unexplored areas that warrant further attention from scholars and practitioners alike. Our study provides a robust framework for categorizing and organizing the platform ecosystem literature, enabling researchers to better understand the underlying connections and relationships between different research streams. This facilitates more efficient knowledge accumulation and dissemination, contributing to the ongoing development and maturation of the field.