Evaluation of Regional Innovation Capacity Based on Social Network Analysis and Entropy-Based GC-TOPSIS

Abstract

Regional innovation capacity is an important indicator used to measure the comprehensive development level of a region. This study aims to assess Hainan’s regional innovation capacity, develop practical strategies for its enhancement, and foster economic growth. Panel data for Hainan from 2010 to 2020 are selected, social network analysis is used to qualitatively screen the indicators of regional innovation capacity, analytic hierarchy process and entropy weight method are used to combine and assign weights to the evaluation indicators, and TOPSIS and the grey correlation methods are used to construct an evaluation model of, and empirically analyse, the regional innovation capacity of Hainan. These three methods, namely, the social network analysis, TOPSIS, and grey correlation methods, complement each other’s strengths and improve the reliability of evaluation results. Their combined use has not been explored in previous studies. The empirical analysis showed that Hainan’s regional innovation capacity has slowly increased, the two indicators—innovation output and innovation economic performance—have significantly improved Hainan’s regional innovation capacity, and the fluctuating growth in Enterprise innovation capability has led to a short-term decline in Hainan’s regional innovation capacity. The findings of this study should assist managers and policymakers in making strategic and tactical decisions for the innovative development of the Hainan region to promote its sustainable development.