Identification of the causal relationship between features and barriers of product–service systems based on Bayesian network model

Abstract

Product-service systems (PSS) potentially offer a promising avenue for balancing resource efficiency improvement and economic growth to achieve sustainability. To successfully implement and operate PSS, early identification and mitigation of implementation barriers are required for enhanced social acceptability. To this end, determining the interrelationship between designing PSS features and potential barriers is crucial. Existing research focused on the PSS attributes and its barriers in isolation, falling short of a holistic understanding of their causal relationships. This paper aims to fill this gap by amalgamating case study data from literature survey and subsequently constructing a Bayesian network model. By establishing a graphical model and probability table, this study identified the stochastic dependencies between PSS features and barriers. This approach not only captures their relationship but also assists in predicting potential barriers based on PSS characteristics during the design phase. The results of this study are expected to furnish PSS designers with a tool for anticipating and addressing implementation barriers, thereby facilitating the successful implementation of PSS.