چكيده لاتين
Abstract
One of the most important parameters for the development of the technology ecosystem is how to finance entrepreneurs and technology-based enterprises. Securing the necessary financial resources for the growth of knowledge-based companies in an appropriate manner and at the right time is one of the key concerns of every technology ecosystem today. Currently, more than 10,000 knowledge-based companies are registered in the country, operating in various fields, and analyzing these companies can yield valuable insights. One of the challenges facing entrepreneurs and policymakers is the lack of proper understanding of the factors contributing to the success and failure of these companies, with financing being one of the most critical aspects. Knowledge-based companies require different types of financing depending on various factors, including the type of product and services, market conditions, prevailing economic circumstances, and most importantly, their product life cycle (whether in the ideation stage, laboratory production, mass production, etc.). Unfortunately, despite the significance of this issue in the country, empirical studies on how to secure financial resources in this area have not been conducted.
The subject of this research is to examine the impact of the financing methods employed by knowledge-based companies on their success and failure. Other control variables will also be analyzed. Therefore, in this study, we will attempt to assess the success and failure of these companies based on available information concerning financing methods, human resources, sales volume, and the history of activities of knowledge-based companies present in the Isfahan Science and Technology Town. The effect of control variables on financing conditions will also be examined.
To investigate the research questions, regression and logistic regression methods will be used. In logistic regression, the dependent variable is a Bernoulli variable indicating the companyʹs success or failure. The independent variables include area of activity, years of activity, number of employees, sales volume, financing methods such as attracting investors, debt (receiving loans), and internal resources (shareholders). Given the significant impact of the COVID-19 pandemic, this variable will also be included in the model.
Keywords: Startup companies, Financing Innovation, Financing Knowledge-BasedCompany, Logistic Regression.
