Evaluating the Performance of the Government Venture Capital Guiding Fund Using the Intuitionistic Fuzzy Analytic Hierarchy Process

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Xu, Jianjun
Yu, Lijie
Gupta, Rakesh
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2020
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http://creativecommons.org/licenses/by/4.0/
Abstract

The performance evaluation of the government venture capital guiding fund (GVCGF) has come into focus in the field of venture capital. Most of the existing studies, such as whether the GVCGF has guided social capital to start-up enterprises and has played its due role in the process of enterprise growth and innovation, are all based on relevant work under the framework of econometric analysis. Unlike in these existing studies, we construct the performance analysis model of the GVCGF from four dimensions, including the standardization development of the guidance fund, the risk control ability, and the leverage and the support effects under the framework of a multi-attribute decision-making analysis. Taking a GVCGF project in Ningbo City, China, as an example, we comprehensively evaluate the development performance of the GVCGF using the intuitionistic fuzzy analytic hierarchy process (IFAHP). The results show that the development performance of the GVCGF is at a "relatively high" level. Compared with the traditional analytic hierarchy process (AHP), the IFAHP effectively avoids the false, enlarged influence caused by data subjectivity and evaluation uncertainty. This study provides a feasible analytical framework for the application of the IFAHP in other project performance evaluations.

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Sustainability
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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Built environment and design
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Xu, J; Yu, L; Gupta, R, Evaluating the Performance of the Government Venture Capital Guiding Fund Using the Intuitionistic Fuzzy Analytic Hierarchy Process, SUSTAINABILITY, 2020, 12 (17), pp. 6908
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