[目的/意义]通过系统识别影响算法采纳的关键因素，构建一个整合性的理论模型，以深入揭示其内在的行为生成机制，应对当前算法采纳研究碎片化、缺乏系统性理论框架的现状。[方法/过程]采用系统性文献综述与程序性扎根理论相结合的研究方法。遵循PRISMA规范，对Web of Science与CNKI两大核心数据库的文献进行系统检索与筛选，最终纳入77篇文献。通过开放编码、主轴编码与选择性编码的程序性分析，对文献内容进行归纳、提炼与整合，识别出核心影响因素，并构建理论模型。[结果/结论]识别出影响算法采纳的17项关键因素，并构建了一个包含外部环境、算法技术、主体与任务适配四个维度的整合性影响因素模型。该模型揭示了算法采纳是一个多维驱动的动态过程：外部环境提供制度约束与社会支持，算法技术决定其内在效能与可信度，主体构成采纳行为的内在驱动系统，而任务适配则是连接各维度并决定采纳行为最终能否实现的关键枢纽。

[Purpose/significance] By systematically identifying key factors influencing algorithm adoption, this study constructs an integrated theoretical model to deeply reveal its underlying behavioral generation mechanism, addressing the current fragmented landscape of algorithm adoption research and the lack of a systematic theoretical framework.[Method/process] A research approach combining systematic literature review and procedural grounded theory was employed. Following PRISMA guidelines, a systematic search and screening were conducted on literature from two core databases, Web of Science and CNKI, ultimately including 77 articles. Through procedural analysis involving open coding, axial coding, and selective coding, the content of these articles was summarized, refined, and integrated to identify core influencing factors and build the theoretical model. [Result/conclusion] The study identified 17 key factors influencing algorithm adoption and developed an integrated influencing factors model comprising four dimensions: external environment, algorithmic technology, subject, and task fit. This model reveals that algorithm adoption is a dynamically driven, multi-dimensional process: the external environment provides institutional constraints and social support; algorithmic technology attributes determine its intrinsic efficacy and trustworthiness; the subject constitutes the internal driving system for adoption behavior; and task fit acts as a critical nexus connecting all dimensions and determining the ultimate realization of adoption behavior.