Efficiency Analysis of Science and Technology Activities in Large and Medium-Sized Industrial Firms in Guangdong Province: A Stochastic Frontier Approach

Abstract

This study employs a stochastic frontier approach to analyze the efficiency of science and technology (S&T) activities in large and medium-sized industrial firms operating in Guangdong province, a leading hub of industrial innovation and economic development in China. Using firm-level data and econometric techniques, we estimate the technical efficiency and explore the determinants of S&T performance among industrial firms in the region. Specifically, we investigate the extent to which factors such as firm size, R&D expenditure, human capital, industry characteristics, and government support influence the efficiency of S&T activities. By applying a stochastic frontier model, we distinguish between the inefficiency arising from random factors and the inefficiency attributable to managerial and operational practices. The findings provide valuable insights into the drivers of S&T efficiency in Guangdong's industrial sector and offer implications for policymakers, industry practitioners, and researchers seeking to enhance the effectiveness and productivity of S&T investments and activities. Moreover, the study contributes to the broader literature on industrial innovation, regional development, and efficiency analysis in the context of China's evolving economy.