Analysis of Customer Churn Behavior in Digital Libraries. Issue 4 (19th August 2014)

• Record Type: Journal Article
• Authors: Lai, Yuangen; Zeng, Jianxun
• Editors: Sicilia, Miguel-Angel; Tsiflidou, Effie
• Is Part Of: Program. Volume 48:Issue 4(2014)
• Publication Date: 2014-08-19
• Subjects: Libraries, University and college -- Great Britain -- Automation -- Periodicals; 025.30285
• DOI: 10.1108/PROG-08-2011-0035
• Languages: English
• ISSNs: 0033-0337

Abstract

Abstract : Purpose: To discuss issues related to customer churn behavior in digital libraries and demonstrate the successful application of Survival Analysis for understanding customer churn status and relationship duration distribution between customers and libraries. Design/methodology/approach: The study applies non-parametric methods of Survival Analysis to analyze churn behaviors of 8054 customers from a famous Chinese digital library, and a cluster method to make customer segmentation according to customer behavioral features. Findings: The customer churn rate of the given library is very high, so as to the churn hazard in early three months after customer's registration on the website of the library. There is clear difference in both customer survival time and churn hazard among customer groups. It is necessary to strengthen customer churn analysis and customer relationship management for digital libraries. Research limitations/implications: The studied samples are mainly based on customers from one digital library and some hypotheses have not been strictly proven due to the absence of relevant empirical researches. Practical implications: This study provides a reasonable basis for decision-making about customer relationship management in digital libraries. Originality/value: Most previous researches about information behavior concentrate on information seeking behavior in digital libraries, seldom discuss customer switching behavior. The paper discusses issues related to customer churn analysis and illustrates the adaptation of Survival Analysis to understand customer churn status and relationship duration distribution in digital libraries.