Analysis on Influencing Factors of Grain Yield under the Grain Supply Chain in Heilongjiang

Limited agricultural production combined with the increasing food demand has led to the Grain Supply Chain instability and food supply conflicts, particularly in Heilongjiang province, a major grain-producing region of China. Increasing grain yield has become the key area of study among researchers. This study constructs a Multiple Linear Regression model based on Stepwise Regression analysis with R software and Eviews to investigate eight factors influencing grain yield in Heilongjiang province from 1992 to 2022 by utilizing methods such as White-test, Durbin-Watson Test, and Variance Inflation Factor to validate this model. According to the findings, an increase in Grain Sown Area, Effective Irrigated Area, and Value Added in Primary Industry, correlates with an increase in Grain Yield. In contrast, an increase in Disaster-Affected Areas and Employment in Primary Industry is associated with a decrease in Grain Yield. In addition, an in-depth analysis regarding the negative coefficient associated with Employment in the Primary Industry was conducted by integrating the Law of Diminishing Marginal Returns. It was concluded that the incompatibility of the initial hypothesis may be attributed to the educational level of Employment in Primary Industry and the efficiency of grain production. To establish a more stable, efficient, and flexible Grain Supply Chain system, it is recommended to enhance resource utilization, strengthen disaster monitoring, control inefficient labor productivity, and promote industrial collaboration to satisfy the increasing demand for boosted Grain Yield.