Analysis of Agricultural Resource Allocation and Market Response Based on Different Crop Yield Data

In the context of promoting rural revitalization, a crop planting strategy was developed for the diverse farmland and rich crop varieties in North China, aiming to adapt to market demand, and land characteristics, and respond to market dynamics and uncertainty. This paper developed a comprehensive planting strategy model that not only provides scientific decision support but also has flexibility and applicability, allowing for adjustments based on actual conditions. The model used the ideal point method and the maximum-minimum model to solve the dual-objective planning problem and evaluated the performance of different planting schemes in a variable environment based on an analysis of data sets. It ultimately determined the optimal planting scheme that could maintain a high yield under the influence of various uncertain factors. The establishment and application of this model can not only help farmers make the most optimal planting choices in complex and variable market and climate conditions but also significantly improve land utilization efficiency and economic benefits, providing strong scientific support for rural revitalization.

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Publication Details

Journal
Highlights in Business Economics and Management
Published
2025-02-27
DOI
https://doi.org/10.54097/kfppk689
Primary Topic
Agricultural risk and resilience
Type
article
Field-Weighted Citation Impact
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article

Analysis of Agricultural Resource Allocation and Market Response Based on Different Crop Yield Data

Yurui Huang, Mingming Zhao, Kuijun Zhao
Highlights in Business Economics and Management
Agricultural risk and resilience
article

Analysis of Agricultural Resource Allocation and Market Response Based on Different Crop Yield Data

Yurui Huang, Mingming Zhao, Kuijun Zhao
article en

Abstract

In the context of promoting rural revitalization, a crop planting strategy was developed for the diverse farmland and rich crop varieties in North China, aiming to adapt to market demand, and land characteristics, and respond to market dynamics and uncertainty. This paper developed a comprehensive planting strategy model that not only provides scientific decision support but also has flexibility and applicability, allowing for adjustments based on actual conditions. The model used the ideal point method and the maximum-minimum model to solve the dual-objective planning problem and evaluated the performance of different planting schemes in a variable environment based on an analysis of data sets. It ultimately determined the optimal planting scheme that could maintain a high yield under the influence of various uncertain factors. The establishment and application of this model can not only help farmers make the most optimal planting choices in complex and variable market and climate conditions but also significantly improve land utilization efficiency and economic benefits, providing strong scientific support for rural revitalization.

Highlights in Business Economics and ManagementVol. 51
Openalex Percentile: Top 90%
Agricultural risk and resilience
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