Exploring the interdisciplinary connections between statistics and reader psychology: Insights into reading behavior

This study explores the borrowing patterns of 3,142 readers who accessed 1,170 statistics books over ten years (2014-2023), resulting in 8,896 book borrowings. To analyze user behaviors, K-means clustering identified three groups of readers based on cumulative borrowing frequency and three groups of books based on their borrowers and borrowings. Correspondence analysis revealed relationships between book and reader types, offering insights into their associations. Factor analysis was employed to identify underlying factors within various book categories, utilizing the Chinese library classification system. A logarithmic transformation was applied to the total borrowings to adhere to the assumptions of normality, facilitating linear regression analysis. Results indicate that the popularity of statistics books in Nanjing Normal University stems from the escalating significance of data literacy, the interdisciplinary integration of statistical methods, and technological advancements in education. Reader Group 3 emerged as the largest engaged cohort, with significant interactions across various book categories. Targeted promotions for Book Groups 1 and 3, aimed at Reader Group 1, could effectively enhance user engagement by reflecting their borrowing preferences. Conversely, a tailored understanding of Reader Group 2's interests can facilitate more focused outreach initiatives. The research also reveals distinct influences on borrowing decisions among different reader types, with varying preferences for interdisciplinary and straightforward scientific content. This study enhances the understanding of borrowing habits while providing methodological insights into applying advanced statistical techniques within library science, emphasizing the importance of targeted engagement strategies.