Wang Li, Ma Jun-Chao, Jiang Zhi-Qiang, Yan Wanfeng, Zhou Wei-Xing
School of Business, East China University of Science and Technology, Shanghai 200237, China.
Zhicang Technologies, Beijing 100016, China.
Entropy (Basel). 2021 May 20;23(5):637. doi: 10.3390/e23050637.
Using a unique data set containing about 15.06 million truck transportation records in five months, we investigate the highway freight transportation diversity of 338 Chinese cities based on the truck transportation probability pij from one city to another. The transportation probabilities are calculated from the radiation model based on the geographic distance and its cost-based version based on the driving distance as the proxy of cost. For each model, we consider both the population and the gross domestic product (GDP), and find quantitatively very similar results. We find that the transportation probabilities have nice power-law tails with the tail exponents close to 0.5 for all the models. The two transportation probabilities in each model fall around the diagonal pij=pji but are often not the same. In addition, the corresponding transportation probabilities calculated from the raw radiation model and the cost-based radiation model also fluctuate around the diagonal pijgeo=pijcost. We calculate four sets of highway truck transportation diversity according to the four sets of transportation probabilities that are found to be close to each other for each city pair. It is found that the population, the gross domestic product, the in-flux, and the out-flux scale as power laws with respect to the transportation diversity in the raw and cost-based radiation models. It implies that a more developed city usually has higher diversity in highway truck transportation, which reflects the fact that a more developed city usually has a more diverse economic structure.
利用一个包含五个月内约1506万条卡车运输记录的独特数据集，我们基于从一个城市到另一个城市的卡车运输概率(p_{ij})，研究了中国338个城市的公路货运运输多样性。运输概率是根据基于地理距离的辐射模型及其基于行驶距离（作为成本代理）的成本版本计算得出的。对于每个模型，我们都考虑了人口和国内生产总值（GDP），并在数量上得到了非常相似的结果。我们发现，对于所有模型，运输概率都具有良好的幂律尾部，尾部指数接近0.5。每个模型中的两个运输概率围绕对角线(p_{ij}=p_{ji})分布，但通常不相同。此外，从原始辐射模型和基于成本的辐射模型计算出的相应运输概率也围绕对角线(p_{ij}^{geo}=p_{ij}^{cost})波动。我们根据四组运输概率计算了四组公路卡车运输多样性，发现对于每对城市，这四组运输概率彼此接近。研究发现，在原始和基于成本的辐射模型中，人口、国内生产总值、流入量和流出量与运输多样性呈幂律关系。这意味着一个更发达的城市通常在公路卡车运输方面具有更高的多样性，这反映了一个更发达的城市通常具有更具多样性的经济结构这一事实。
