Technology investment and industrial development: A neural-network simulation

Abstract

Using data from a 13-year period panel, this study analyzes the interaction of Taiwan's technology investment and industrial development, through the training and extraction of a multi-layered, feed-forward neural network. The simulation experiments provide a reference behavior pattern for China, while accounting for its culture-specific context. Also analyzed are the potential effects of technology investment on the GDP and employment rates of China's primary and tertiary industries. The simulation results show that the basic-research budget percentage could positively affect China's tertiary industry, yet increasing both the basic-research budget percentage and the research and development (R&D) personnel could decidedly increase the GDP rate of China's primary industry. Following the study's limitations, explored are its potential implications for policymaking and future research.