Efficiency Analysis of Scientific and Technological Innovation in Grain Production Based on Improved Grey Incidence Analysis

Abstract

Analyzing and evaluating the efficiency of scientific and technological innovation in grain production is conducive to the rational allocation of resources, promoting the development of scientific and technological innovation in grain production and providing guarantee for grain security. By refining the elements of grain production and scientific and technological innovation, an evaluation system of scientific and technological innovation in grain production is constructed. Firstly, combining linear programming together with the traditional grey synthetic incidence analysis model, a incidence analysis of the scientific and technological innovation indicators of grain production is carried out, and the key and secondary indexes affecting grain outputs are screened by an improved grey incidence analysis model. Secondly, based on DEA-Malmquist index model and taking the grain production process as the research object, the scientific and technological achievement transformation indicators are divided into pre-production, in-production and post-production indicators. The key indicators and secondary indicators of scientific and technological innovation of grain production in various cities of Henan Province from 2010 to 2019 are used to analyze the efficiency of scientific and technological innovation in each stage of grain production. The results show that: (1) The type of basic ability of scientific and technological innovation indicators and the transformation ability of scientific and technological innovation achievements are the major indicators influencing grain outputs, and the investment of basic resources of scientific and technological innovation and the transformation of scientific and technological innovation achievements are the most important to improve grain outputs. (2) In addition, the study reveals that the secondary indicators of the technological innovation efficiency of grain production based on the DEA-Malmquist index model are more efficient than the key indicators in the pre-production, in-production and post-production stages. And there are gaps in the scientific and technological innovation performance of grain production among cities in Henan Province, and the index of technological progress is the leading factor for the gap.

The evaluation of grey relative incidence

“…The GIA is commonly used for solving problems in engineering (Kokocińska et al ., 2020), natural and social sciences (Nowak et al ., 2020). Example applications of GIA models in the recent years include: service quality analysis in healthcare (Javed and Liu, 2018), the Industry 4.0 research (Fahim et al ., 2021), green supplier selection (Quan et al ., 2018), project management (Javed and Liu, 2019), grain production (Zhang et al ., 2021), research on the effect of electrification on the level of economic development (Nowak et al ., 2021), research on the development of science and technology (Wei and Wu, 2016), research on sustainable development (Yi et al ., 2021; Kaswan and Rathi, 2021), research on social media (Weng et al ., 2021), research on customer satisfaction (Peng et al ., 2021; Xiang, 2022), business performance analysis (Škrinjarić and Šego, 2021; Ellibeş and Candan, 2021), corporate social responsibility analysis (Diaz and Nguyen, 2021), quality management (Valmohammadi et al ., 2021), or financial management (Ramezani, 2022). In general terms, within the relational analysis in the grey system theory, we distinguish distance-, surface-, and panel-based models (Liu et al.…”