[Purpose/significance] The introduction of SOR theory in the field of library and Information Science (LIS) in China has achieved phased achievements. When it refers to SOR theory, related researches have discussed the con? notation and basic framework of it. In order to provide further reference for the normative application of SOR theory in LIS research, this paper attempts to systematically review the current domestic literature on the application of SOR the? ory in LIS research. [Method/process] The study analyzes the traceability, three-dimensional characteristics, applica? tion topics and application process of SOR theory in LIS field in China, aiming to clarify the applicability, advantages and limitations of SOR theory. [Result/conclusion] The results show that the majority of literature mainly focuses on the topic of information behavior, and the interpretation of factors and relations of stimulus and organism dimension can be divided into "direct interpretation" and "cooperative interpretation with other theories or models". In terms of theo? retical coordination, the stimulus dimension is mainly extended by the theories about "the behavior and motivations of users", while the organism dimension is combined with the theories about "the cognition and emotion of users", and the response dimension is developed from two perspectives of "approach- avoidance". Application topics include virtual knowledge community, social and business platform, mobile government platform and online platform of university li? brary, etc. And there are some differences in the core variables of each topic. Research design has a distinct characteris? tic of "method- process", which can be divided into qualitative, quantitative and mixed processes. Based on the re? search review, this paper proposes some suggestions for the future application of SOR theory in LIS field, such as using the theory critically, focusing on the antecedents of the stimulus dimension, expanding research of the organism and re? sponse dimension, and improving dynamic measures and data objectivity.