[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.