Modeling Uncertainties Associated with Single-Valued Neutrosophic Multi-Attribute Decision-Making for Performance Evaluation of Risk Investment in Small and Medium-Sized High-Technology Venture Enterprises
Year: 2024
Type: article
Abstract: In recent years, a group of rapidly growing technology-based entrepreneurial enterprises have emerged in China, playing an increasingly important role in the national economy. However, small and medium sized technology startups have low profitability and high risk, making it difficult to obtain sufficient funds from traditional financing channels. At present, research on venture capital evaluation mainly focuses on the evaluation of projects before venture capital, and empirical methods are mostly used to study the promoting effect of venture capital on performance after investment, ignoring the issue of continuous evaluation after investment. The performance evaluation of risk investment in small and medium-sized high-technology venture enterprises is MADM. In such study, the generalized weighted geometric Bonferroni mean (GWGBM) technique is illustrated for MADM under single-valued neutrosophic sets (SVNSs). We begin by constructing the single-valued neutrosophic number GWGBM (SVNNGWGBM) operator, followed by the introduction of the MADM based on this technique. Subsequently, we provide an illustrative example that evaluates the performance of risk investment in small and medium-sized high-technology venture enterprises, supplemented by some comparative analyses to demonstrate the SVNNGWGBM technique. The principal contributions of this research are highlighted: (1) The maximizing deviation method is employed to derive the weight; (2)The GSVNNWBM technique is developed, setting the stage for the introduction of MADM methods based on GSVNNWBM technique; (3) Numerical example is presented that focuses on the performance evaluation of risk investment in small and medium-sized high-technology venture enterprises, along with a comparative decision analysis.
Authors: Huihui Shi, Ting Li, Fan Yang, Lei Qiao
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6892959359
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