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北京市出租车需求量测算与数量规制——基于课题组调查问卷和官方数据的测算 被引量:3

Demand Calculation and Quantity Regulation of City Taxi:Take Beijing as an Example
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摘要 基于课题组的问卷调查统计和官方数据,采用主成分回归法和供需平衡法组合测算了北京市出租车的合理数量。若行驶速度和空驶率不变,2017年出租车的合理存量是128447辆,缺口近6万辆。当行驶速度提高到平均50公里/小时,已有存量才能满足需求。在使用移动平台APP后,供需匹配率提高,空驶率明显下降。当空驶率大幅度降为10%时,合理供给量为79060辆,缺口为10576辆。测算结果显示,在运营边际效率很难有较大幅度提高的情况下,应放松进入管制,允许更多进入,并允许和鼓励“快车”“专车”和“顺风车”等基于移动互联网平台的替代者的边缘性进入;在放松进入管制的同时,对出租车服务市场的规制应由进入和价格规制转向以安全和质量为重点的社会性规制上。 Based on the questionnaire survey and official data of the research group,this paper uses the combination of the principal component analysis method and the supply and demand balance forecasting method to predict the demand for taxis in Beijing.In 2017,if the rate of empty vehicle running and driving speed was unchanged,the demand was 128,447,while the actual number was 68,484,with a shortage of nearly 60,000.In theory,when the average driving speed increases to 50 km/h,the stock of taxis can match with the demand.After using the mobile platform APP,the matching ratio of supply and demand increases,and the air-driving rate significantly reduces.When the vacancy rate drops significantly to 10%,the reasonable supply is 79,060 and the shortage is 10,576.The calculation result shows that,the entry control should be loosened to allow more entry,and the marginal entry of substitutes based on mobile Internet platforms such as“express”,“special car”and“hitch ride”should be allowed and encouraged under the background of the difficulties of significantly improving the operation efficiency at the margin.At the same time,the regulation of rental market should be changed from economic regulation to social regulation focusing on safety and quality.
作者 孟昌 庞燕岭 MENG Chang;PANG Yan-ling(School of Economics, Beijing Technology and Business University, Beijing 100048, China)
出处 《北京社会科学》 CSSCI 北大核心 2020年第5期4-16,共13页 Social Sciences of Beijing
基金 北京市社会科学基金项目“北京市出租车市场管制下的租金耗散与管制改革”(14JGB029)。
关键词 北京市出租车需求量 供需平衡法 主成分回归分析法 组合测算 taxi demand in Beijing the supply and demand balance calculating method the principal component analysis method combined forecast
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