Unveiling the Algorithmic Modeling and Knowledge Structure of Smart Product-Service Systems: A Hybrid Analytical Approach

Source abstract

Smart Product-Service Systems are a crucial paradigm that integrates digital technologies into traditional product-service systems, yet a detailed analysis of their knowledge structure and development is missing. To bridge this gap, the current study performs a systematic review of 804 scholarly publications. Through mathematical modeling techniques combining bibliometric analysis and advanced machine learning algorithms, this study sources annual publication trends, institutional and author collaboration networks, co-citation patterns and the thematic structure of research topics. Our findings organize the field into three thematic groups distinguished by semantic distance: strategic and business dimensions of Smart Product-Service Systems encompassing servitization and sustainability, system design and industrial implementation, and SmartPSS-specific design methods covering requirement elicitation, conceptual design and evaluation. Method-oriented research in Smart Product-Service Systems remains concentrated in specialized design science traditions, underlining the need to extend formal evaluation frameworks and requirement engineering approaches toward broader industrial and service ecosystems. Future efforts must be focused on translating theoretical advancements into integrated, scalable solutions to real-world challenges that also promote sustainability. This study not only contributes to gaining a holistic understanding of the Smart Product-Service Systems domain through computational modeling but also provides some directional insights for future researchers and practitioners to guide more focused and impactful future studies.