Explore and evaluate innovative value propositions for smart product service system: A novel graphics-based rough-fuzzy DEMATEL method

Abstract

Abstract The rapid development of advanced information and communication technology enables the mainstream trend of manufacturing value propositions towards smart product service system (PSS). Prospect innovative value propositions (IVPs) emerge in the context of smart PSS. The IVPs analysis plays a critical role in the successful planning and design of smart PSS business model, which includes two key steps: identification and evaluation. However, the existing research rarely systematically explore what value propositions can be identified in the emerging field of smart PSS. Thus, this study conducts a comprehensive IVPs identification through literature review and prioritize these IVPs to provide support for later smart PSS concept design. Compared to other evaluation methods, the Decision Making Trial and Evaluation Laboratory (DEMATEL) presents higher effectiveness to evaluate the interrelationship and importance degree of the identified IVPs. Moreover, the previous fuzzy-based DEMATEL is feasible to handle intrapersonal uncertainty (individual linguistic vagueness), and the previous rough-based DEMATEL can effectively manipulate the interpersonal uncertainty (group preference diversity). Nevertheless, there are few researches on simultaneous manipulation of the two kinds of uncertainty which may lead to inaccurate evaluation results. Therefore, this study develops a novel graphics-based rough-fuzzy DEMATEL method for IVPs evaluation. The effectiveness and accuracy of the proposed evaluation method are illustrated through the application in the smart vehicle service system and the comparisons with several different methods. The proposed evaluation model can provide more accurate and informative results, because it integrates the merits of fuzzy set in coping with the intrapersonal uncertainty and the strength of rough set in handling interpersonal uncertainty, and supports to present decision inconsistency along with the final weights based on a proposed graphics-based operator.