Public Management
saeed chehreh; Mohammadali Sarlak; Ashraf Rahimian
Abstract
The current research was done with the aim of designing a model to improve the performance of start-up accelerators and identifying its dimensions and components. This research is in the category of mixed exploratory research in terms of practical purpose and in terms of method. The current research ...
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The current research was done with the aim of designing a model to improve the performance of start-up accelerators and identifying its dimensions and components. This research is in the category of mixed exploratory research in terms of practical purpose and in terms of method. The current research was carried out in two parts: qualitative (supercomposition and Delphi) and quantitative. The population studied in the qualitative section includes 25 Persian and Latin articles related to the improvement of performance in startups, which were selected by the census method in the meta-composite method. The statistical population in the Delphi section included 30 management faculty members and managers of companies related to start-up accelerators. In the quantitative section, 250 samples of accelerator employees were selected using a systematic random stratified method. The data collection tool is a questionnaire, the validity of which was obtained and confirmed through the methods of construct validity and factor loadings, as well as the calculation of Cronbach's alpha. In order to analyze the data, exploratory and confirmatory factor analysis as well as path analysis were used using spss and smart pls statistical software. Based on exploratory factor analysis, 73 questionnaire items have been 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 start-up accelerators.
Maryam Gholizadeh; Mohammad Ali Sarlak
Abstract
Knowledge intensive business services (KIBS) are known to play a significant role in innovation systems. Past research has however mostly treated KIBS as a homogenous group; it is now time to understand better the variety that exists among KIBS. The main purpose of this study was the classification of ...
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Knowledge intensive business services (KIBS) are known to play a significant role in innovation systems. Past research has however mostly treated KIBS as a homogenous group; it is now time to understand better the variety that exists among KIBS. The main purpose of this study was the classification of knowledge intensive business services by distinguishing their knowledge bases (analytical, synthetic or symbolic). In this Delphi study, after reviewing previous research and examining the upstream documentation and infrastructure at ABFA, the areas of knowledge associated with a description of business services were identified. The results of data analysis showed that in all knowledge areas identified including creation, upgrading and development of water and wastewater facilities, center of supervision, operation and maintenance of facilities, sales and customer service, supply and support management, human resources management, management Financing, partner relationship management, developing management systems have analytical and synthetic knowledge.
