Dynamic user profile construction and its application to smart product-service system design: A maternity-oriented case study

Abstract

The human-centric philosophy is considered a crucial development direction for smart Product-Service Systems (smart PSS). Smart PSS has effectively advanced the circular economy by enhancing user experience, incorporating servitization and digital servitization, and extending product lifecycle, among other key aspects of sustainable development. However, there is currently a lack of a reasonable, accurate, and actionable framework and methodology to express the human element, namely user profiling, within this philosophy. To address this gap, this paper utilizes statistical methods such as factor analysis, cluster analysis, and regression analysis, building upon the concept of traditional user profiling. The aim is to integrate the three prominent approaches of goal-oriented, scenario-based, and data-driven user profiling, with the goal of complementing each other and designing a top-level user profiling framework for smart PSS. Furthermore, Industry 4.0 technologies and text mining techniques are employed to collect data on users' product and service usage. As these data contain real-time information about user needs, behaviors and goals at different time periods, they can be used to construct dynamic features of user profiling, and ultimately achieve the construction of dynamic user profiling for smart PSS. To validate the proposed user profiling framework and dynamic user features of smart PSS, this paper presents a case study focusing on the user group of maternal women. This case study promotes the in-depth exploration of smart PSS research in expressing the human element.