大数据背景下农产品滞销的指标体系构建及风险等级评定——基于DEMATEL与灰色预测模型的研究

The Index System Construction and Risk Rating of Unsalable Agricultural Products Based on Big Data

通过分析我国2012年至2017年发生的120个农产品滞销事件,从农产品供应链的生产、销售和运输三个关键环节和农产品滞销的主观、客观和不确定三大类九小类实质原因两个维度,建立了农产品滞销因素的供应链——实质原因(SC-RC)判别与定位矩阵,寻找农产品滞销的主要因素,并使用DEMATEL方法定位其中最关键的因素,再通过AHP-模糊综合评价法构造了预测农产品滞销风险等级的量化指标和计算公式,利用灰色预测模型预测了2019年陕西酥梨滞销风险的等级,从而验证该评价方法的科学性。

This paper analyzes the 120 unsatisfactory sales of agricultural products from 2012 to 2017 in China, from the three key links of production, sales and transportation of agricultural product supply chain and the subjective, objective and uncertain three categories of agricultural products. Two dimensions, the establishment of the supply chain of the slow-moving factors of agricultural products-the physical cause(SC-RC) discriminant and positioning matrix, to find the main factors of agricultural products slow-moving, and use the DEMATEL method to locate the most critical factors;and then through the AHP-fuzzy comprehensive evaluation, the method constructs a quantitative index and calculation formula for evaluating the unsalable risk level of agricultural products. Finally, the grey prediction model is used to predict the level of the slow-selling risk of Shanxi pears in 2019, thus verifying the scientificity of the evaluation method.