Research on Segmentation of Car-buying Users Based on Cross-industry Data Integration: Tianjin Car Buyers as Case

Xing Han (), Ziran Dong (), Qiuhao Li () and Taige Hu ()
Additional contact information
Xing Han: China Automotive Technology & Research Center Co. Ltd., Automotive Data of China Co. Ltd
Ziran Dong: China Automotive Technology & Research Center Co. Ltd., Automotive Data of China Co. Ltd
Qiuhao Li: China Automotive Technology & Research Center Co. Ltd., Automotive Data of China Co. Ltd
Taige Hu: China Automotive Technology & Research Center Co. Ltd., Automotive Data of China Co. Ltd

A chapter in Proceedings of the 2024 6th International Conference on Economic Management and Model Engineering (ICEMME 2024), 2025, pp 227-237 from Springer

Abstract: Abstract Through the integration of two authoritative data resources and the construction of auto-user related big data, this study employes hierarchical cluster method to analyze Tianjin’s vehicles buyers from 2014 to 2022. The present study centered on family-associated labels and addressed challenges due to data asynchrony and collection anomalies by data preprocessing techniques and feature engineering. As a result, users are categorized into nine distinct groups, including five majority groups and four minority groups. The study finds that different groups are significantly different in car-purchasing behavior. Factors such as family structure and economic status affect car purchase decisions. This research offers a novel user research classification approach for the Chinese automotive market. This study also provides theoretical support and practical guidance for automotive enterprises based on big data user segmentation.

Keywords: big data; hierarchical clustering; vehicle buyer; family structure; co-built label system (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-690-1_22

Ordering information: This item can be ordered from
http://www.springer.com/9789464636901

DOI: 10.2991/978-94-6463-690-1_22

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().