A Smart Model for Financing Startups with Blockchain, Case Study: HamiChain Platform

Document Type : Case Study & Methodology

Authors

• Mohammad Hossein Sobhani ¹
• Seyed kazem Ebrahimi ¹
• Peyman Akhavan ²

¹ Faculty Of Economics, Management And Administrative Sciences, Semnan University, Semnan, Iran

² Department of Management and Industries,Qom University Of Technology, Qom, Iran

10.22067/ijaaf.2023.43011.1216

Abstract

Encrypted assets can be traded like traditional currencies, and products and services can be exchanged for digital currencies. The use of  SMART contracts in the context of the blockchain network allows startups to be able to finance creative projects. In this research, a qualitative-quantitative approach has been used. Meta-synthesis method was used to identify smart financing indicators for startup businesses. In the quantitative stage, the importance of the extracted indicators was collected by distributing questionnaires among 220 investors and the project team and analyzed with the help of SPSS software and One-Sample T-tests, and Friedman's ranking. The results showed that among the 7 indicators of the intelligent model extracted from the qualitative method, the indicators of implementation, trust, and results are considered the most critical dimensions from the respondents' point of view in intelligent financing. Also, the indicators of confidence, participation, and cognition are next in importance, and the belief index was ranked seventh. The proposed model covers 78% and 80% of the opinions of the investors and the project team. Among the advantages of the proposed model are fast, safe, and transparent financing, diversity in investment method choices, project interaction, SMART contracts, and a pattern of reward distribution to network members instead of transaction fees. A blockchain-based financing model can provide startups with a quick and low-cost path to growth and development.

Keywords

• Encrypted Assets
• SMART Financing
• HamiChain
• Startup

Main Subjects

• Finance

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©2023 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

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