A chance discovery-based approach for new product-service system (PSS) concepts

As a product-service system (PSS) attracts much attention as an alternative for sustainable development, studies have suggested ways to support the PSS development process. Despite the growing interest of PSS, however, little attention has been paid to generating PSS concepts from large-scale customer behaviors, situations, and relevant needs (BSNs) regarding a product. Although understanding customer BSNs comprehensively is the most prerequisite and fundamental in PSS development, the previous literature assumes that the identification of customer BSNs is completed or imputed to manual and intrinsic tasks by experts, such as customer surveys and interviews, which may be time-consuming and costly. Therefore, this paper proposes an approach to identifying new PSS concepts by combining the chance discovery theory and text mining of Web news. The approach helps PSS designers identify significant customer BSNs from massive news data over a wide-scope regarding a given product, and it facilitates PSS designers to ideate about PSS scenarios and concepts efficiently by providing breaking events which can act as PSS chances. To illustrate the working process of our approach, a case using Web news of electric bicycles is introduced. The proposed approach will contribute to the ideation process for new PSS concepts; it further holds the potential to create a synergetic effect in case of being incorporated into the existing PSS development methodologies.