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The purpose is to explore the essential reasons for the differences between book awakening phenomena, to develop the critical factors in awakening the slumbering collections and to provide a reliable basis for maximizing book value and optimizing collection allocation.

The research employs the integrated learning algorithm XGBoost to measure driving factors. In the process of book circulation, the characteristics of collections and readers are worthy of attention. Therefore, this study also carries out feature selection and model construction from the two dimensions of books and readers.

The results show that reader features have a stronger impetus for the collection awakening phenomenon than collection features. Among reader features, education level, gender and major subject are the main factors, which are followed closely by the activity level; among collection features, publication date and price are the main driving factors. The indicators of book popularity are not significant, whose effect on the phenomenon of collection awakening is almost negligible.

This study aims to augment the theory of zero circulation from the theoretical level and, for the first time, seeks to define the phenomenon of collection awakening. This study attempts to present novel ideas for research in the field of libraries and to provide references for optimizing collection and maximizing the value of books.