Technological innovation efficiency and its impact factors: An investigation of China?s listed energy companies

This study empirically examines the technological innovation efficiency (TIE) and its influencing factors using a multiple input-output stochastic frontier analysis model and a fixed-effect model on a sample of China's listed energy companies between 2008 and 2017. The results revealed the following. (1) The number of patents and research and development investments of China's listed energy companies increased rapidly. However, the overall TIE level of these energy companies was far lower than that of the effective state and showed a downward trend. (2) For the enterprise classification samples, the TIE of state-owned and foreign energy enterprises was lower than that of private energy enterprises, and the TIE of new energy enterprises was higher than that of traditional energy enterprises. (3) For the patent classification samples (IPC1, IPC2, and IPC3), only an increase in IPC2 (the number of patents in fixed buildings, mechanical engineering, heating, weapons, and blasting fields) helped increase the TIE of energy enterprises. (4) Government subsidy and financial leverage are positive factors, while financing constraints, market uncertainty and asset size are negative factors for increasing the TIE of energy enterprises.

Automated summary

This study empirically examines the technological innovation efficiency (TIE) of China's listed energy companies and its influencing factors. The results show that the overall TIE level of these energy companies is low and decreasing, with state-owned and foreign energy enterprises having lower TIE than private energy enterprises, and new energy enterprises having higher TIE than traditional energy enterprises. Increasing the number of patents in the IPC2 field has a positive impact on improving the TIE of energy enterprises. Government subsidy and financial leverage are positive factors for increasing TIE, while financing constraints, market uncertainty, and asset size are negative factors.