Abstract
This article takes the evaluation model of data envelopment analysis (DEA) and Malmquist index change and its decomposition method, from 2014 to 2018, of sugarcane production in 8 cities in Guangdong province as the research object and the selection of sugarcane production output and production factors as a model output variable and input variable, respectively, according to the eight cities of Guangdong province in 2014–2018 statistics and analyzes the sugarcane production efficiency of 8 cities in Guangdong province. The research results show that there are significant differences in the regional development level of sugarcane production comprehensive efficiency and the regional development imbalance of sugarcane industry in the eight cities of Guangdong province. The lower TPI of the eight cities is mainly due to the lower level of technological innovation. So as to put forward countermeasures which are university resource orientation for the sugarcane comprehensive efficiency in cities less than 1, transportation and telecommunication infrastructure, enhancement of the strength, the establishment of Guangdong province agricultural science and technology innovation alliance, and increase in sugarcane industry with modern manufacturing and the butt joint degree of the international marketing environment, the government actively build international BBS in sugarcane industries.
Highlights
Guangdong is one of the three major sugarcane-producing areas in China
In the extensive application of the data envelopment analysis (DEA) relative efficiency evaluation method, THE BCC model assumes that the decision unit (DMU) is variable production scale return (VRS), and the pure technical efficiency value (PTE) can be obtained. e CCR model assumes that the production status of DMU is fixed scale reward (CRS), and the overall technical efficiency value (TE) can be obtained
Based on the analysis model of the Malmquist index and its decomposition index adopted in this paper, the author used Stata 15.0 software to measure the output and input data of sugarcane production in 8 cities in Guangdong province, analyzed its spatial-temporal variation characteristics [13], and obtained corresponding analysis results (Tables 4–6)
Summary
In the past five years, the planting area and total output of sugarcane in Guangdong ranked third in China after Guangxi and Yunnan. According to the report data provided by the “Forecast of China’s Sugar Consumption from 2015 to 2030”, China’s domestic sugar shortage may increase to nearly 13 million tons in the 10 years, further deepening the severe challenge faced by China’s sugar supply and demand balance. To ensure the supply of sugar to meet the increasing demand of the phase and improve the market competitiveness of domestic sugarcane, improve the standard of peasants’ daily life, promote rural modernization
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