Unveiling the Determinants of Book Renewals: An Interdisciplinary Exploration using Factor and Regression Analysis

Abstract

This paper aims to comprehensively analyze readers' borrowing and renewal behaviors, explore the influencing factors, and provide data-driven support for library resource allocation and borrowing policy formulation. Focusing on readers' borrowing data, the study first classifies the data based on whether there is a book renewal behavior and segments it into three periods (2016-2018, 2019-2021, 2022-2024). Then, various statistical methods, such as Logarithmic Transformation, Principal Component Analysis (PCA), Z-score, Binary Logistic Regression, Quantile Regression, and moderation effect analysis using the PROCESS macro for SPSS, are applied. The research reveals that the distribution of total book borrowings and renewals shows that most data cluster around lower volumes with some high-value outliers, and the median values remain relatively stable over time. Different factors have diverse impacts on book renewal and borrowing behaviors; for instance, in different periods, variables like reader types and gender have varying influences on renewal behavior, and in the quantile regression analysis of LogTotal, different variables exhibit different significance levels at different quantiles. This study provides a detailed and systematic multi-perspective analysis using multiple statistical methods, offering new insights into understanding reader behavior patterns and guiding libraries to optimize resource management and formulate more targeted borrowing policies.