Research on the Driving Factors of Regional Innovation Quality Based on Multiple Linear Regression Model

Abstract

The efficiency of urban green development is deeply rooted in the innovation capabilities of urban clusters. Adhering to innovation-driven strategies to lead green development enhances the innovation quality of urban clusters. This study employs grey comprehensive evaluation to select indicators that represent innovation quality and establishes a principal component regression model for researching the driving factors of innovation quality in the Yangtze River Delta urban cluster. Empirical research is conducted using data related to the overall green innovation quality driving factors for 41 cities in the Yangtze River Delta from 2010 to 2020. The study indicates that the regional gross domestic product (GDP) is the most representative indicator of innovation quality. Factors such as technological research and development, the number of patents, economic foundations, and business development exhibit significant positive effects, while environmental planning, management systems, human capital, and international openness show significant negative effects. To enhance the innovation quality in the Yangtze River Delta, it is essential to address the deficiencies in policy and market-driven approaches. Emphasizing green, high-quality development, taking into consideration both economic and ecological benefits, enhancing technological innovation capabilities, and aligning expansion of business plans with environmental planning are key strategies. Additionally, optimizing the structure and quality of higher education, making sensible investments in human capital, and focusing on the quality of foreign capital inflow are crucial steps towards achieving this goal.