Dynamic elicitation and forecasting innovation requirement of smart product-service system via user-manufacturer value co-creation perspective using multi-source data

Achieving greater efficiency and lower resource consumption is a constant pursuit for successfully developing smart product-service system (PSS). Conducting dynamic requirements analysis is increasingly important in the process while the value co-creation of smart PSS stakeholders has not been sufficiently considered. This study adopts a user-manufacturer value co-creation perspective to explore smart PSS dynamic requirement elicitation and forecasting. Using multi-source data of user online reviews, historical descriptive texts and patent abstracts, this study dynamically elicits the smart PSS innovation requirements using dynamic topic model (DTM) and bidirectional encoder representation from transformers (BERT). Furthermore, the key innovation requirements of smart PSS are identified by integrating their importance and satisfaction values into a dynamic importance- performance analysis (DIPA). Then, the trend of smart PSS key innovation requirements is predicted by the grey forecasting model to determine the smart PSS improvement direction. An empirical study of smartwatch service system is conducted to validate the proposed approach. By blending both user and manufacturer requirements, this study provides a novel framework for dynamic requirement elicitation and forecasting of smart PSS based on multi-source data. It contributes to facilitating the value co-creation during smart PSS development to optimize manufacturer's R&D &D resource allocation and enhance user experience.