Study on the total factor productivity and its influence factors of food processing industry：Based on the perspective of artificial intelligence and agricultural efficiency

doi:10.14088/j.cnki.issn0439-8114.2022.10.030

Abstract

Abstract: Based on the provincial panel data from 2009 to 2019, the total factor productivity（TFP） and its decomposed indices of Chinese food processing industry by using the DEA-Malmquist method were calculated and then the influence mechanism and degree of artificial intelligence and agricultural efficiency on TFP under the fixed-effect model were examined. The results showed that the TFP of the food processing industry as a whole showed an upward trend during the study period, mainly driven by technological progress, but the growth rate fluctuated and decreased; the growth rate was the highest in the southern coastal region and the lowest in the northeast region of Chinese economic regions; artificial intelligence had positive effects on technological progress but inhibited TFP, and the “productivity paradox” existed in Chinese food processing industry; agricultural efficiency contributed to the growth of TFP by positively influencing technical efficiency. Accordingly, the countermeasures and suggestions of promoting the transformation and upgrading of the food processing industry, developing complementary AI technologies in the food processing industry and building modern agriculture were put forward.

Key words: food processing industry, total factor productivity, artificial intelligence, agricultural efficiency

CLC Number:

F426.82

SHEN Dan-hong, ZHAO Xiao-nan. Study on the total factor productivity and its influence factors of food processing industry：Based on the perspective of artificial intelligence and agricultural efficiency[J]. HUBEI AGRICULTURAL SCIENCES, 2022, 61(10): 165-172.

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