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Tehnički vjesnik, Vol. 25 No. 6, 2018.

Izvorni znanstveni članak
https://doi.org/10.17559/TV-20180720122815

Auto Insurance Business Analytics Approach for Customer Segmentation Using Multiple Mixed-Type Data Clustering Algorithms

Kai Zhuang ; Donlinks School of Economics and Management, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing 100083, China
Sen Wu ; Donlinks School of Economics and Management, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing 100083, China
Xiaonan Gao ; Donlinks School of Economics and Management, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing 100083, China

Puni tekst: engleski, pdf (1 MB) str. 1783-1791 preuzimanja: 39* citiraj
APA 6th Edition
Zhuang, K., Wu, S. i Gao, X. (2018). Auto Insurance Business Analytics Approach for Customer Segmentation Using Multiple Mixed-Type Data Clustering Algorithms. Tehnički vjesnik, 25 (6), 1783-1791. https://doi.org/10.17559/TV-20180720122815
MLA 8th Edition
Zhuang, Kai, et al. "Auto Insurance Business Analytics Approach for Customer Segmentation Using Multiple Mixed-Type Data Clustering Algorithms." Tehnički vjesnik, vol. 25, br. 6, 2018, str. 1783-1791. https://doi.org/10.17559/TV-20180720122815. Citirano 19.02.2019.
Chicago 17th Edition
Zhuang, Kai, Sen Wu i Xiaonan Gao. "Auto Insurance Business Analytics Approach for Customer Segmentation Using Multiple Mixed-Type Data Clustering Algorithms." Tehnički vjesnik 25, br. 6 (2018): 1783-1791. https://doi.org/10.17559/TV-20180720122815
Harvard
Zhuang, K., Wu, S., i Gao, X. (2018). 'Auto Insurance Business Analytics Approach for Customer Segmentation Using Multiple Mixed-Type Data Clustering Algorithms', Tehnički vjesnik, 25(6), str. 1783-1791. doi: https://doi.org/10.17559/TV-20180720122815
Vancouver
Zhuang K, Wu S, Gao X. Auto Insurance Business Analytics Approach for Customer Segmentation Using Multiple Mixed-Type Data Clustering Algorithms. Tehnički vjesnik [Internet]. 2018 [pristupljeno 19.02.2019.];25(6):1783-1791. doi: https://doi.org/10.17559/TV-20180720122815
IEEE
K. Zhuang, S. Wu i X. Gao, "Auto Insurance Business Analytics Approach for Customer Segmentation Using Multiple Mixed-Type Data Clustering Algorithms", Tehnički vjesnik, vol.25, br. 6, str. 1783-1791, 2018. [Online]. doi: https://doi.org/10.17559/TV-20180720122815

Sažetak
Customer segmentation is critical for auto insurance companies to gain competitive advantage by mining useful customer related information. While some efforts have been made for customer segmentation to support auto insurance decision making, their customer segmentation results tend to be affected by the characteristics of the algorithm used and lack multiple validation from multiple algorithms. To this end, we propose an auto insurance business analytics approach that segments customers by using three mixed-type data clustering algorithms including k-prototypes, improved k-prototypes and similarity-based agglomerative clustering. The customer segmentation results of these algorithms can complement and reinforce each other and demonstrate as much information as possible to support decision-making. To confirm its practical value, the proposed approach extracts seven rules for an auto insurance company that may support the company to make customer related decisions and develop insurance products.

Ključne riječi
auto insurance; business analytics approach; clustering; customer segmentation; mixed-type data

Hrčak ID: 212835

URI
https://hrcak.srce.hr/212835

Posjeta: 70 *