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基于公路货运市场监测的铁路运价调整机制研究 被引量:2

Railway Freight Rate Adjustment Mechanism Based on Roadway Freight Market Monitoring
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摘要 针对铁路货运缺乏市场竞争力的问题,研究公铁竞争环境下铁路货运定价策略。首先搭建多种运输方式市场监测可视化平台,监测公路货运市场,分析公路货运量及运价随线路、季节、市场供需、运输成本等因素的变化趋势,并构建基于ARIMA模型和SVM模型的公路市场运价驱动预测模型,捕捉运价变化的时间序列特征以及市场因素对运价的影响,对公路货运周运价进行预测。在公路货运价格预测的基础上,根据预测结果,在公铁竞争的市场条件下,提出基于Logit模型的公铁竞争定价机制,通过求解得到铁路货运建议定价。研究对于铁路运输企业完善价格决策体系、提高铁路货运市场竞争力、降低社会物流成本具有重要的现实意义。 For the lack of market competitiveness of railway freight,this paper studied the pricing strategy of railway freight in a competitive environment.Firstly,a visual platform for market monitoring was built for various transportation modes to monitor the highway freight market and analyze the variation of the road freight volume and freight price with factors such as route,season,market supply and demand,and transportation cost.The paper built a prediction model driven by highway market freight rate based on the ARIMA model and the SVM model to capture the time series characteristics of freight rate changes and the influence of market factors on freight rate and predict the weekly freight rate of highway freight.According to the highway freight rate forecast,the competitive pricing mechanism of highway and railway based on the Logit model was proposed under the market conditions of highway and railway competition,and the suggested pricing of railway freight was obtained by calculation.The research is of great practical significance for improving the price decision-making system of railway transportation enterprises,promoting the market competitiveness of railway freight,and reducing the cost of social logistics.
作者 张双霞 李丹丹 凌霞 ZHANG Shuangxia;LI Dandan;LING Xia(Freight Transport Department,China Railway Lanzhou Group Co.,Ltd.,Lanzhou 730031,Gansu,China;School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 611756,Sichuan,China)
出处 《铁道货运》 2022年第5期6-13,共8页 Railway Freight Transport
基金 中国铁路兰州局集团有限公司科技项目(2021016-2)。
关键词 铁路运价 竞争定价 市场监测 ARIMA模型 SVM模型 LOGIT模型 Railway Freight Rate Competitive Pricing Market Monitoring ARIMA Model SVM Model Logit Model
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