Blockchain-Enabled Fundraising for SMEs: A Systematic Literature Review on Emerging Token-Based Financing Models for Small and Medium-Sized Enterprises

سال انتشار: 1404
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 82

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شناسه ملی سند علمی:

MBVET04_004

تاریخ نمایه سازی: 12 مهر 1404

چکیده مقاله:

Small and medium-sized enterprises (SMEs) often face acute barriers in accessing capital, including limited collateral, regulatory burden, and exclusion from traditional financial ecosystems. This study systematically examines the potential of blockchain-enabled fundraising mechanisms such as token-based financing, decentralized crowdfunding platforms, and trust-enhancing supply chain solutions to address these constraints. Employing a systematic literature review (SLR) complemented by thematic meta-synthesis, the paper analyzes ۱۱ peer-reviewed studies across three integrated thematic streams: (۱) token-based fundraising architectures, (۲) blockchain-enabled transparency and trust for SME finance, and (۳) smart contract-driven crowdfunding infrastructures. Findings reveal a fragmented but evolving research landscape, with strong conceptual innovation but limited empirical validation, especially within SME-specific contexts. The review surfaces key adoption challenges related to regulatory interoperability, digital capability gaps, and scalability limitations in resource-constrained environments. By framing SMEs as active design constraints rather than passive adopters, the study advances a socio-technical alignment perspective that integrates institutional theory, design science, and FinTech systems thinking. The article concludes with theoretical contributions, managerial and policy implications, and a future research agenda aimed at co-developing inclusive, scalable, and legally robust blockchain fundraising solutions for SMEs.

نویسندگان

Neda Seyedin Hashemi

Faculty of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Aylar Ziapour Sohi

Department of Computer Engineering and Artificial Intelligence, Islamic Azad University, Karaj Branch, Karaj, Iran

Araz Saie Arasi

Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran

Aidin Ziapour Sohi

Department of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran