..., this study deconstructs enterprise digital transformation into six characteristics and measures these characteristics using data from listed industrial companies between 2016 and 2020. Various machine learning methods, such as cluster analysis and Bayesian networks, are applied to explore the complex impact...

... knowledge, then combine expert knowledge with big data and the proposed fuzzy interpretive structural model (FISM) and K2 are used for expert knowledge acquisition and big data learning, respectively. The Bayesian network (BN) obtained is used for forward inference and backward inference. Data from Lending...

... of this paper is to propose a model-driven approach to optimal freeze sequence identification based on change propagation risk. Design/methodology/approach – A dynamic Bayesian network was used to represent the change propagation process within a system. According to the model, when a freeze decision...

...Youngim Bae; Hyunjoon Chang Purpose This study aims to identify factors that determine the smart TV buying decisions of users and analyze the relationships among the factors by using Bayesian network approach. Design/methodology/approach This study investigates smart TV users' perception based...