International Comparison of the Efficiency of Agricultural Science, Technology, and Innovation: A Case Study of G20 Countries

Agricultural and innovation policies aimed at mitigating climate change

The EU supports agricultural policies to help farmers meet the challenges of climate change (CC) by promoting more sustainable and environmentally friendly practices. This study focuses on the European primary sector (agriculture, forestry, and fisheries), productive activities that meet humanity's basic needs, although this sector does not account for a dominant share of GDP. The analysis uses a panel data sample of 22 European countries for the period 2012-2019, and seeks to answer the following research questions: Is there a direct relationship between agricultural innovation efficiency and the technological advances implemented? What effect do GHG emissions and innovation efficiency have on CC? Which agricultural practices have the greatest effect on the volume of GHG emissions? The results indicate that the European primary sector has registered an average rise in productivity of 4%, mainly driven by technological improvements. This underscores the need for agricultural innovation policies that focus not only on improving aspects related to technology but also on making better use of existing resources. In addition, the econometric models estimated confirm that efficiency levels are the most influential determinants of temperature change, while GHG emissions are primarily explained by their own historical values. Ultimately, research and development is a tool that can be used to curb CC, along with the proper use of land and fertilizers. There is thus a need to foster novel agricultural practices that help reduce emissions while ensuring the efficiency of the sector.

Research on the Efficiency of Green Agricultural Science and Technology Innovation Resource Allocation Based on a Three-Stage DEA Model-A Case Study of Anhui Province, China

In order to achieve sustainable development of agriculture, people have gradually begun to attach importance to the development of low-carbon agriculture and to regard green agricultural technology innovation and promotion as increasingly more important. Taking the Anhui Province of China as an example, this study analyzed the impact of green agricultural science and technology innovation resource allocation on rural revitalization by constructing an econometric model. We found that the overall efficiency of the overall allocation of agricultural science and technology innovation resources in Anhui Province increased in the sample period, but the scale efficiency level was relatively low. The key path to improving the overall efficiency of allocation was to improve the scale efficiency level. The allocation of agricultural science and technology innovation resources in 16 cities and prefectures performed well in terms of pure technical efficiency, but there were significant differences in scale efficiency, which further affected the overall allocation efficiency of different regions. Among them, the allocation efficiencies of agricultural science and technology innovation resources in Hefei and Fuyang were at the leading level in Anhui Province. Similar to the overall situation of the province, the improvement path of areas with low comprehensive efficiency lay in the improvement of scale efficiency. In view of this, from the policy level, we need to optimize the relationship between the government and the market, speed up the construction of platforms and carriers, attach importance to the construction of the agricultural science and technology talent training system, and improve the open sharing mechanism.

Measurement of Innovation Efficiency in China’s Electronics and Communication Equipment Manufacturing Industry-Based on Dynamic Network SBM Model

In recent years, China’s electronics and communication equipment manufacturing (ECEM) industry has overgrown, and the government should assess the innovation performance of the industry for its sustainable development. However, most previous studies on the innovation efficiency of the ECEM industry have ignored the link and carry-over variables. This paper uses the number of patent applications as a link variable to consider the stage of innovation activities. It divides the innovation activities of the electronics industry into two stages: technology development and results in transformation. To consider the dynamics of innovation activities, this paper uses capital stock as a period carry-over variable and evaluates the change of innovation efficiency over time. In this paper, the DNSBM model is used to measure the innovation efficiency of the ECEM industry in 26 Chinese provinces from 2013–2019. This model includes both stage link variables and period carry-over variables, thus allowing for overall efficiency and stage efficiency and period efficiency. The results show that the overall innovation efficiency values in the Chinese ECEM industry are low, there are considerable differences between the two-stage efficiency values in the east, central and western regions, and the overall efficiency values show a slow upward trend.