The Analysis of Logistics Situation in Beijing-Tianjin-Hebei

The Analysis of Logistics Situation in Beijing-Tianjin-Hebei

International Journal of Trend in Research and Development, Volume 4(2), ISSN: 2394-9333 www.ijtrd.com The Analysis of Logistics Situation in Beijing-Tianjin-Hebei 1Hengliang Tang, 2Jie Li and 3Ying Liu 1,2,3School of Information, Beijing Wuzi University, Beijing, China Abstract-- This paper does a descriptive study on spatial billion 260 million yuan, accounting for 10% of the whole distribution of logistics situation in Beijing-Tianjin-Hebei country. area.It shows that Tianjin has the largest freight tonnages, In this paper, authors will present the development status of following by Tangshan, Handan, and Shijiazhuang. Beijing logisitics in Beijing-Tianjin-Heibei areas. The description and Tianjin have the largest post volumes, following by method and hierarchical clustering method are used to analyze Shijiazhuang, Baoding, and Tangshan. Beijing has the largest the logistics status in 13 cities of this area. The three variables number of employees, following by Tianjin, Shijiazhuang, and of each city such as freight tonnages, post volumes, and Tangshan. For all the other cities in Hebei, they have low employees in transportation industries are chosen for analysis. values in all the three columns. Hierarchical Clustering is then used to group 13 cities of this area into 4 groups. Cluster 1 and II. HIERARCHICAL CLUSTERING 2 are the two well-developed clusters in logistics situations, Hierarchical clustering essentially consists of progressively cluster 3 is the median-developed cluster in logistics situations. organizing all of the candidate objects into clusters comprising However, cluster 4 is the low-developed cluster in logistics mutually similar objects as determined by some measure of situations. inter-object and inter-cluster similarity, proceeding in Keywords-- Logistics situation; Beijing-Tianjin-Hebei; succession from the formation of small clusters containing just Hierarchical Clustering two objects to large clusters containing many objects. It is characteristic of this procedure that the clusters formed in each I. INTRODUCTION step can be graphically displayed in tree diagrams referred to The concept of logistics was first established in the United as dendrograms. Hierarchical clustering is widely used as it States. It originated in 1930s, and it originally meant "physical visuality, but it is less efficient for large observations. In this distribution" or "goods distribution". In 1963, it was paper, the dataset only has 13 observations and 3 columns, and introduced into Japan. Japanese means "circulation of each observation represents a main city, while each column substances". After 1970s, the word "logistics" in Japan represents the freight tonnages, post volumes, and employees gradually replaced the "circulation of things".The basic in transportation industries. The dataset is suitable for function of logistics industry in national economy is to achieve hierarchical clustering method. The data are transformed by z- commodity circulation. In the circulation of goods,Logistics is score standardized before clustering. By clustering, the 13 the concrete embodiment of the material transformation main cities are grouped into several cluster, and the analysis process to be solved in the process of commodity exchange. about these cluster is then performed. The result is useful to The size of logistics capability, including the capacity of show the difference and similarity of these 13 observations. transportation, packaging, loading and unloading, storage and III. SPATIAL DISTRIBUTION OF LOGISTICS distribution, directly determines the scale and speed of the STATUS IN BEIJING-TIANJIN-HEBEI AREAS circulation of goods. The situation of commodity circulation directly affects the market supply of commodities, and it restricts the satisfaction degree of people's consumption demand. The efficiency and cost of commodity circulation determine the market competitiveness of a company and the competitiveness of the country's commodity. Under the current market economy, the cost of logistics has become bigger and bigger. It has become the main factor determining the production cost and circulation cost. Beijing, Tianjin and Hebei is the "capital economic circle" of China, including Beijing, Tianjin city and Baoding, Tangshan, Langfang, Shijiazhuang, Qinhuangdao, Zhangjiakou, Chengde, Cangzhou, Handan, Xingtai, and Langfang. Among them, Beijing, Tianjin, Baoding and Langfang are the core functional areas in the central part of China. Beijing, Tianjin and Hebei are connected with each other in terms of human affinity, regional integration and culture, and also with a profound historical origin and a suitable communication radius, thus they can be fully integrated and coordinated. Beijing, Tianjin and Hebei, located in the heart of Bohai in the Northeast Asia, is the largest and most dynamic region in the north of China. It Figure 1: The spatial distribution of freight tonnages of all the has attracted more and more attention from China and the cities in Jing-Jin-Ji areas. whole world. In 2016, the total GDP of three regions of Beijing, Tianjin and Hebei amounted to 7 trillion and 461 Figure 1 shows the spatial distribution of freight tonnages of IJTRD | Mar – Apr 2017 Available [email protected] 839 International Journal of Trend in Research and Development, Volume 4(2), ISSN: 2394-9333 www.ijtrd.com all the cities in Jing-Jin-Ji areas. It can be found that Tianjin has the largest freight tonnages, following by Tangshan, Handan, and Shijiazhuang. All these cites are the transportation center for around areas, and except Shijiazhuang the remaining 3 cites all have ports for ocean shipping. Chengde and Hengshui have the lowest freight tonnages, and their values are about 1/10 of Tianjin’s. It is because these two cities are not industrial cities and they have no many requirements for freights. However, Beijing as the capital of China has median freight tonnages, and it is affected by the government’s police that removing the non-core functions of the capital. Figure 3: The spatial distribution of employees in transportation industries of all the cities in Jing-Jin-Ji areas. IV. THE CLUSTER ANALYSIS ON LOGISTICS STATUS IN BEIJING-TIANJIN-HEBEI AREAS After the Hierarchical Clustering, the tree-diagram are shown in Figure 4, and it demonstrate how the areas are grouped into small groups in detail. The three variables of each city such as freight tonnages, post volumes, and employees in transportation industries are chosen for cluster. From the figure 4, the 13 cities are grouped into 4 sub-groups. Beijing and Tianjin are in cluster 1 and 2 respectively; Tangshan, Handan, and Shijiazhuang are in the cluster 3, and all the remaining cities are in cluster 4. Beijing and Tianjin are Figure 2: The spatial distribution of post volumes of all the two metropolis, and their logistics economical structures are cities in Jing-Jin-Ji areas. different from the other cities in Hebei, thus they should not be grouped with Hebei cities. However, in freight tonnages and Figure 2 shows the spatial distribution of post volumes of all the number of employees in transportation industries, Beijing the cities in Jing-Jin-Ji areas. It can be found that Beijing and is quite from Tianjin, so it is reasonable that they are in Tianjin have the largest post volumes, following by separate clusters. For the other cities in Hebei, Tangshan, Shijiazhuang, Baoding, and Tangshan. Post volumes are Handan, and Shijiazhuang are the more developed cities, and mainly determined by citizens daily consuming, and all these their logistics situations are different from the other cities in cities are richer in this areas, especially for Beijing and Hebei. For example, their values in freight tonnages, post Tianjin. Beijing and Tianjin are two municipalities directly volumes, and employees in transportation industries are larger under the Central Government, and people of these two cities than other the Hebei cities. That is the reason why Hebei cities often have high demands for postal service. Zhangjiakou, are grouped into two separate clusters. Chengde and Xingtai have lowest postal volumes, as their economic are developed in a low scale, and people living there do not have enough savings for consuming. In all, rich cities often have high postal volumes. Figure 3 displays the spatial distribution of employees in transportation industries of all the cities in Jing-Jin-Ji areas. It can be found that Beijing has the largest number of employees, following by Tianjin, Shijiazhuang, and Tangshan.The amount of employees is mainly determined by citizens daily consuming, and in Beijing the web shopping orders are much higher than other cities.Tianjin has a high postal volumes, but they are mainly on ocean shipping, thus not high amount of employees are required. For all the other cities in Hebei, their numbers of employees in transportation industries are not high. It is because their population level and consuming amount are low and not high number of employees is required. Figure 4: The tree-diagram of Hierarchical Clustering on logistics situations. IJTRD | Mar – Apr 2017 Available [email protected] 840 International Journal of Trend in Research and Development, Volume 4(2), ISSN: 2394-9333 www.ijtrd.com control technology research; University Cultivation Fund Project of 2016-Research on Congestion Model andalgorithm of picking system in distribution center. References [1] Chen, Zhijuan, and S. Zhang. "Study on Development Countermeasures for Comprehensive Transportation System in Tianjin under New Situation." Logistics Technology (2015). [2] Dong, Xi Chen, and G. X. Wang. "Coal logistics competency analysis for ports in the Tianjin and Hebei regions around the Bohai bay in China." International Conference on Management Science 2010:436-443. [3] Dustin Schder, Feng Ding, and Juliana Kucht Campos. "The Development Strategy of E-Commerce Logistics in Figure 5: The cluster profile table for all the 4 clusters. Beijing." Open Journal of Social Sciences 03.11(2016):99-105. It can be seen from Figure 5 that cluster 1 have low value in [4] Hai-Sheng, K. E., Y. Zhang, and T. N. University.

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