As an important component of the postal industry, the courier industry presents a wide range of industrial fields, absorbing a large number of jobs, high economic added value, significant technical features and other diverse characteristics. It integrates various functions such as information transmission, goods delivery, capital circulation and cultural communication, and involves many fields such as production, circulation, consumption, investment and finance, which is an irreplaceable basic industry in modern society. Therefore, based on the current situation of express industry development, this paper explores the index system affecting express business volume, and selects the national express business income, GDP per capita, fixed asset investment in tertiary industry, total wholesale and retail trade, online shopping transactions, total export trade, total import trade, transportation, storage industry, postal business income, the proportion of urban areas in the resident population, urban The 13 indicators, such as the total mileage of delivery routes, cargo turnover, total road mileage, population density, number of Internet users, etc., are compared by using MATLAB software to find out the key factors affecting the development of the express industry by comparing the gray correlation coefficients, and putting forward policy suggestions to promote the regional development of the express industry in order to provide reference for the development of the national express industry. The results of the correlation coefficients were obtained through the grey correlation coefficient comparison.
Published in | American Journal of Management Science and Engineering (Volume 7, Issue 5) |
DOI | 10.11648/j.ajmse.20220705.12 |
Page(s) | 75-81 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2022. Published by Science Publishing Group |
Grey Correlation Model, Express Industry, Influencing Factors, High-Quality Development
[1] | Choi Y. The efficiency of major ports under logistics risk in Northeast Asia [J]. Asia-Pacific Journal of Operational Research, 2011, 28 (01), pp. 111-123. |
[2] | Reiner G, Teller C, Kotzab H. Analyzing the Efficient Execution of In-Store Logistics Processes in Grocery Retailing-The Case of Dairy Products [J]. Production and Operations Management, 2013, 22 (4), pp. 924-939. |
[3] | Hayashi K, Nemoto T, Nakaharai S. The Development of the Parcel Delivery Service and its Regulations in China [J]. Procedia-Social and Behavioral Sciences, 2014, 125, pp. 186-198. |
[4] | Zou Shuqi, Hou Yunxian. An empirical study on the factors influencing the development of express delivery industry [J]. Modern Trade Industry, 2014, (01), pp. 70-72. |
[5] | Shang Fengrui, Zhang Jing. Prediction of China's express business volume based on SARIMA model [J]. Modern Economic Information, 2016 (10), pp. 350. |
[6] | Shi Yongmei. Empirical analysis of factors influencing express business volume [J]. Statistics and Management. 2018, (06). |
[7] | Li Shuqin. Research on the forecast of express delivery demand in Anhui Province [D]. Hefei University of Technology, 2020. |
[8] | Xue Rongna, Zhang Mingmin, Nan Yuting, Zhao Huijuan. Daily average courier business volume prediction model based on GRU deep learning algorithm [J]. Statistics and Decision Making. 2021, 37 (13). |
[9] | Deng Julong. Basic methods of gray systems [M]. Wuhan: Huazhong University of Science and Technology Press, 2002. |
[10] | Xie Cui, Li L-M. Correlation analysis of green finance development and carbon reduction efficiency of logistics enterprises in the context of carbon neutrality [J]. Business Economics Research. Business Economics Research. 2022, (10), 2002. |
[11] | Zhang Erli, Kang Dongliang, Gu Lifeng, Ding Lipeng. Development forecast of China's express industry based on GM (1, 1) model for 2019-2024 [J]. Journal of Henan College of Education (Natural Science Edition), 2020, 29 (2): 9-14. |
[12] | Zhu C-F, Xiao S-Y. Research on China's express business volume based on ARIMA model [J]. Mall Modernization, 2020 (2): 25-27. |
[13] | Xiao, Len-Lan, Dai, Hou-Ping. Forecasting express business volume in Hunan Province based on GM (1, 1) model [J]. Science and Technology Perspectives, 2020 (17): 63-65. |
[14] | Wang Lianhua. Gray correlation degree analysis model and its application in China's express delivery industry [J]. Logistics Technology. 2015, Vol. 34, No. 10, pp. 80-82. |
[15] | Li Fengsheng, Du Dongru, Yan Fangfang. Evaluation of science and technology innovation capacity in Heilongjiang Province - based on gray correlation-TOPSIS method [J]. Times Economic and Trade. 2021, 18 (12), pp. 113-115. |
[16] | Liu Yisheng, Li Honglei. An empirical study on the development of China's express delivery industry from the perspective of industrial development [J]. Journal of Capital University of Economics and Trade, 2017 (1): 68-72. |
APA Style
Gan Quan. (2022). Research on the Influencing Factors and Paths of the High-Quality Development of China's Express Industry. American Journal of Management Science and Engineering, 7(5), 75-81. https://doi.org/10.11648/j.ajmse.20220705.12
ACS Style
Gan Quan. Research on the Influencing Factors and Paths of the High-Quality Development of China's Express Industry. Am. J. Manag. Sci. Eng. 2022, 7(5), 75-81. doi: 10.11648/j.ajmse.20220705.12
@article{10.11648/j.ajmse.20220705.12, author = {Gan Quan}, title = {Research on the Influencing Factors and Paths of the High-Quality Development of China's Express Industry}, journal = {American Journal of Management Science and Engineering}, volume = {7}, number = {5}, pages = {75-81}, doi = {10.11648/j.ajmse.20220705.12}, url = {https://doi.org/10.11648/j.ajmse.20220705.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmse.20220705.12}, abstract = {As an important component of the postal industry, the courier industry presents a wide range of industrial fields, absorbing a large number of jobs, high economic added value, significant technical features and other diverse characteristics. It integrates various functions such as information transmission, goods delivery, capital circulation and cultural communication, and involves many fields such as production, circulation, consumption, investment and finance, which is an irreplaceable basic industry in modern society. Therefore, based on the current situation of express industry development, this paper explores the index system affecting express business volume, and selects the national express business income, GDP per capita, fixed asset investment in tertiary industry, total wholesale and retail trade, online shopping transactions, total export trade, total import trade, transportation, storage industry, postal business income, the proportion of urban areas in the resident population, urban The 13 indicators, such as the total mileage of delivery routes, cargo turnover, total road mileage, population density, number of Internet users, etc., are compared by using MATLAB software to find out the key factors affecting the development of the express industry by comparing the gray correlation coefficients, and putting forward policy suggestions to promote the regional development of the express industry in order to provide reference for the development of the national express industry. The results of the correlation coefficients were obtained through the grey correlation coefficient comparison.}, year = {2022} }
TY - JOUR T1 - Research on the Influencing Factors and Paths of the High-Quality Development of China's Express Industry AU - Gan Quan Y1 - 2022/11/14 PY - 2022 N1 - https://doi.org/10.11648/j.ajmse.20220705.12 DO - 10.11648/j.ajmse.20220705.12 T2 - American Journal of Management Science and Engineering JF - American Journal of Management Science and Engineering JO - American Journal of Management Science and Engineering SP - 75 EP - 81 PB - Science Publishing Group SN - 2575-1379 UR - https://doi.org/10.11648/j.ajmse.20220705.12 AB - As an important component of the postal industry, the courier industry presents a wide range of industrial fields, absorbing a large number of jobs, high economic added value, significant technical features and other diverse characteristics. It integrates various functions such as information transmission, goods delivery, capital circulation and cultural communication, and involves many fields such as production, circulation, consumption, investment and finance, which is an irreplaceable basic industry in modern society. Therefore, based on the current situation of express industry development, this paper explores the index system affecting express business volume, and selects the national express business income, GDP per capita, fixed asset investment in tertiary industry, total wholesale and retail trade, online shopping transactions, total export trade, total import trade, transportation, storage industry, postal business income, the proportion of urban areas in the resident population, urban The 13 indicators, such as the total mileage of delivery routes, cargo turnover, total road mileage, population density, number of Internet users, etc., are compared by using MATLAB software to find out the key factors affecting the development of the express industry by comparing the gray correlation coefficients, and putting forward policy suggestions to promote the regional development of the express industry in order to provide reference for the development of the national express industry. The results of the correlation coefficients were obtained through the grey correlation coefficient comparison. VL - 7 IS - 5 ER -