Designing Native Decision-Making Model for Selecting Venture Capital Investment in Emerging Companies
الموضوعات :
Mohammadreza Radfar
1
(Department of Financial Management,Central Tehran Branch,Islamic Azad University,Tehran, Iran.)
Gholamreza Zomorodian
2
(Department of Business Management, Central Tehran Branch , Islamic Azad University, Tehran, Iran.)
Mansoureh Aligholi
3
(Department of Business Management, Central Tehran Branch , Islamic Azad University, Tehran, Iran.)
Mehrzad Minouei
4
(Department of Industrial Management, Central Tehran Branch , Islamic Azad University, Tehran,Iran)
Farhad Hanifi
5
(Department of Business Management, Central Tehran Branch , Islamic Azad University, Tehran, Iran.)
الکلمات المفتاحية: Economic Growth, Entrepreneurs, Risk, Venture Capital,
ملخص المقالة :
Venture capital companies play an important role in the economy of countries and greatly influences economic and employment growth. VC is the provision of capital for companies and entrepreneurs that is prone to leaping and growing value and, of course, a lot of risk. However, the volume of venture capital in our country is far less than the economic capacity. Many of analysts consider having no model for venture capital in our country as the main reason for this. Therefore, the present study by the qualitative method aims to design decision-making native model for selecting venture capital investment in emerging companies. To achieve this goal, by collecting qualitative data through literature reviews and having deep interview with experts and venture capital firms, a native decision-making model for selecting venture capital in emerging companies is presented. The methodology of this research based on purpose, is fundamental and through the qualitative methods, thematic analysis method is used. Purposeful sampling method is used and interviewing experts continued to theoretical saturation level that means the number of selected samples includes 16 elites. The native decision-making model for selecting venture capital in emerging companies presented in this research has 16 main themes and 86 sub-themes.
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