Competition Strategy of Crowdsourcing Logistics Service Quality Based on Big Data Technology

DOI

10.2991/978-94-6463-198-2_93How to use a DOI?

Keywords

Big Data; Crowdsourcing Logistics; Logistics; RayData

Abstract

“Big data” has become a century-old keyword and will comprehensively involve all aspects of economic and social life. Big data is a leap in data storage and processing capabilities in the Internet era. In the era of big data, logistics companies are listed as one of China's top ten emerging service industries. As one of the national development strategic industries supporting my country's economic growth, the development of the crowdsourcing logistics industry is still lagging behind. Therefore, many logistics companies have encountered a series of opportunities and risks in the process of growth. This paper adopts RayData big data visual interaction system to integrate the volume of express delivery business and express complaints in China. Analyze the development status of crowdsourcing logistics through data visualization technology. From this, four major risk points are summarized: distribution risk, technology risk, service risk and trust risk. In addition, it also focuses on the analysis of the possible role of big data technology in crowdsourcing logistics, including a series of improvements in user experience, logistics cost, distribution efficiency, and human resource allocation. Finally, combined with the above analysis, a set of crowdsourcing logistics service quality competition strategies based on big data technology is proposed. This will help promote the healthy development of crowdsourcing logistics, improve the technical level of important data of logistics companies, and establish a sound regulatory and legal system.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Haiwei Zuo
AU  - Aiqun Zhu
AU  - Shiman Li
AU  - Yanpin Zhu
PY  - 2023
DA  - 2023/08/10
TI  - Competition Strategy of Crowdsourcing Logistics Service Quality Based on Big Data Technology
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 894
EP  - 903
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_93
DO  - 10.2991/978-94-6463-198-2_93
ID  - Zuo2023
ER  -