saeed chehreh

The current research was conducted with the aim of designing a model to improve the performance of start-up accelerators and identify its dimensions and components. This research, in terms of its nature and method, is among mixed exploratory research and has a practical purpose. This research includes two qualitative (supercomposition and Delphi) and quantitative parts. In the qualitative part of the studied community, there were 25 Persian and Latin articles related to the improvement of performance in the accelerator, which were selected by census method with metacombination method. The statistical population in the Delphi section included 30 faculty members in the field of management and managers related to start-up accelerators. In the quantitative part, 250 samples of employees of Iranian accelerators were selected using a systematic random stratified method. Data collection was done using the researcher's questionnaire, the validity of which was obtained and confirmed by the methods of construct validity and factor loadings, as well as the calculation of Cronbach's alpha. For data analysis, exploratory and confirmatory factor analysis as well as path analysis were used using spss and smart pls software. According to the results obtained from exploratory factor analysis, 73 questionnaire items are classified into 12 main components and 61 sub-components. The results of confirmatory factor analysis show that 12 human resources components of coaching, management techniques, customer perspective, continuous improvement, support, financial relations, internal processes, business model, program ecosystem, competitors and environment are effective in improving the performance of startup accelerators.

Today, the present and future success of competition between 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 and knowledge assets. The main foundation of emerging companies and organizations based on knowledge and the use of ideas, creativity, and innovation is the reality of the new business world. The overall purpose of this research identify the effective components of knowledge management in the startups of the field of information science and science and provide a model in this regard. The main purpose of this study is to identify the effective components of knowledge management in startups in the field of information science and epistemology and to provide a model in this regard. This research is applied in terms of purpose and is exploratory mixed research in terms of method. The present 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 information science and 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 information science and science startups and provided further development of such startups.

One of the most widely used fields of knowledge management is the commercialization of knowledge. This research, with the help of scientometric techniques, identifies the effects of knowledge in the field of knowledge commercialization. This research is a kind of scientometric. Initial data were obtained from the Web of Science (WoS) database to investigate the historical roots of published works in the field of commercialization of knowledge. Then, the main roots of this filed, the amount of received citations, and influential works were identified using RPYS software. Next, with the help of the yearcr software, the extent of the effects of the works outside of the range of peaks were also introduced. The period under investigation is the publication in the years 1900-2015. By searching published works in the time period of 1900-2015, 1550 records related to commercialization of knowledge were retrieved. The total number of citations up to the time of the present research was 39817, which resulted in the emergence of five peaks in the years 1934, 1962, 1973, 1998, and 2003. The present project has introduced the influential works in the field of commercialization of knowledge. Identifying the influential effects in the field of commercialization of knowledge makes it possible to identify the main origins and subfields of knowledge.