Today, the present and future success in competition among organizations is based, in part, on the strategic expertise of physical and financial resources and, to a large extent, on the strategic management of knowledge assets. The main purpose of this study was to identify the effective components of knowledge management in startups in the field of knowledge and information science and propose a model in this field. This research is applied in terms of purpose and is an exploratory mixed research in terms of method. This research is applied in terms of purpose and is mixed exploratory research in terms of method. The study was conducted in two parts: qualitative (meta-combination) and quantitative (Delphi and exploratory factor analysis). The population in the qualitative part included Persian and Latin articles related to knowledge management in startups, which were selected according to the inclusion criteria in the meta-combined method. In order to reach a consensus on the components extracted from the meta-combination, the Delphi method and a survey of 30 faculty members in this field were applied. The quantitative section includes 323 examples of startup-related companies in the field of information science and epistemology, which were selected by systematic stratified random sampling method. The data collection tool was a questionnaire whose reliability was confirmed by Cronbach's alpha for the whole questionnaire equal to 0.811. SPSS statistical software was used to do exploratory factor analysis by which 128 items of the questionnaire were classified into 9 main components and 55 sub-components. The results of confirmatory factor analysis show 9 components of knowledge application (23.875), knowledge sharing (11.261), knowledge creation (8.805), organizing knowledge (4.426), knowledge identification (2.820), knowledge presentation (2.684), knowledge development (2.342), knowledge change (2.047), and knowledge protection (1.876) are effective on knowledge management in information science and epistemology startups. Accordingly, knowledge application has the most variance and the knowledge protection has the least variance. Considering the limited studies that have been done in the field of knowledge and information science startups in the country, the results of this research can be used as a model for implementing knowledge management in explaining and recognizing the factors affecting knowledge and information science startups and providing further development in such startups.