It is vital to promote and optimize the technological innovation efficiency of new energy vehicle (NEV) enterprises for the green transformation of China’s automobile industry. However, China’s NEV enterprises still have problems such as insufficient research of technology and unreasonable innovative resource allocation. To improve the technological innovation efficiency of China’s NEV enterprises, the NEVs’ technological innovation process is divided into two stages: the research and development (R&D) stage and the achievement transformation stage in this research. Combining Tobit regression with data envelopment analysis (DEA), an evaluation framework of technological innovation efficiency of the NEV enterprises is constructed. Then, the innovation efficiency of 23 NEV listed enterprises from 2013 to 2018 is analyzed. The result reveals three findings. First, the overall technological innovation efficiency of NEV enterprises is low. Second, enterprises’ R&D efficiency is generally higher than the achievement transformation efficiency. Third, according to two-stage efficiency, 23 NEV enterprises are divided into four categories. For different types of enterprises, targeted guidance to improve innovation efficiency is proposed. This research provides a theoretical and practical basis for improving the innovation efficiency of NEV enterprises.

With the socio-economic development in China, the central government pays more and more attention to innovations. Universities, research institutes, and industries (URI) are the main bodies of innovation. Therefore, in order to perform sustainable development of innovation, it is essential for Chinese policy makers to better understand the relationship among URI innovations. In this paper, indicators for evaluating URI innovations are collected, which are classified into three subsystems. Utilizing regional data from 2009–2015 in China, the entropy method is subsequently used to examine the contribution of indicators to the relative innovation subsystems. Then, a coupling coordination degree model is developed based on the physical concept “coupling” to investigate the relationship of URI innovation subsystems in China. The results reveal that in the period of study: (1) research and development (R&D) input and output indicators are both important to the regional innovation levels of URI, namely, they are critical for improving the coupling coordination degree among the three innovation subsystems; (2) There is an increasing trend of the coupling coordination of URI innovation system in China; however, the gap between regions/provinces becomes larger due to different innovative resource endowments and socio-economic development conditions. The results shown in this paper can provide important implications for policy makers to obtain the sustainable development of URI innovation subsystems in China.

In this paper we study and compare the environmental efficiency of 118 photovoltaic (PV) plants in China. Drawing on the nonparametric data envelopment analysis (DEA) method, our study takes the initiative to take the insolation, annual sunshine duration, and covering area as input variables into account, as well as the installed capacity, annual electricity generation, CO₂ emission reduction, and coal saving as output variables, to provide a unified measure of environmental efficiency of PV plants in China. We find widespread inefficiencies in roughly 95% of the PV plants, and the performance of different economic zones and types of PV plants are quite different. Specifically, those PV plants in eastern China are the least satisfying performers among three different economic zones. The surprising result indicates that eastern China has room for improvement by overcoming the inefficiencies caused by serious aerosol pollution and the high urbanization rate. We also find rooftop PV plants have the highest efficiencies among the four types of PV plants due to very little power loss. However, complementary PV plants have the lowest efficiencies most likely because of high operating temperatures during the process of power generation.

Intellectual property rights protection (IPRP) has caused great concern in China, especially since the introduction of the Belt and Road (B&R) initiative. The Chinese government has increased investments to the countries along the B&R, most of which are developing countries with high investment risks. Using the panel data of China’s outward foreign direct investment (OFDI) in 121 countries from 2003 to 2017, the sustainable relationships between the IPRP of host countries and China’s OFDI has been analyzed. The results of this paper show that, from the worldwide perspective, the stronger the IPRP of the host country, the greater attraction to China’s OFDI. While the IPRP of the countries along the B&R has a nonlinear U-shaped effect on China’s OFDI, which is related to the complex environments of the countries. When the IPRP of the B&R countries is within a certain range, China’s OFDI is biased toward a country with lower IPRP, and when the IPRP exceeds a certain range, China’s OFDI is biased toward a country with higher IPRP. Moreover, the market size, natural resources endowment and political environment of the host country are influential upon China’s OFDI as well. What deserves our attention is that China’s OFDI is more biased towards countries with poor political conditions, which can be related to the enterprise type and that most of the large multinational enterprises in China are state-controlled, resulting in investment decisions largely reflected by the national political goals rather than simple market targets.

Energy transition in the transport sector (TS) is important for the goals of achieving carbon peak by 2030 and carbon neutrality by 2060 in China. A number of scholars have conducted studies to identify the potential energy savings of the TS and to improve its energy efficiency. Most of them concentrate on the direct energy use (EU). The indirect EU along the supply chain of the TS is often neglected. In this paper, the direct and indirect energy use, i.e., the embodied EU, of China’s TS is measured by applying a multi-regional input–output (MRIO) model, where they are investigated from both the provincial and sectoral perspectives. Results show that intermediate use is the major driving force for the TS’s embodied EU in China. From the sectoral level, supply from sectors such as petroleum refining and coking and demand from the service sector are the main reasons of the TS’s embodied EU. From the provincial perspective, the TS’s embodied EU is driven by low transportation technologies in most provinces located in central and western China. By contrast, abundant economic and social activities are the primary reason for the TS’s embodied EU in most provinces in eastern China. In the terms of interprovincial transfer, the energy embodied in the TS flows from resource-intensive provinces located in central and western China to resource-deficient provinces in eastern China. In addition, a close geographical connection exists in the transfer. Finally, several strategies from the sectoral and provincial levels are provided for policymakers.