Using beta regression to explore the relationship between service attributes and likelihood of customer retention for the container shipping industry. (August 2017)

• Record Type: Journal Article
• Authors: Chen, Kee Kuo; Chiu, Rong-Her; Chang, Ching-Ter
• Is Part Of: Transportation research. Volume 104(2017)
• Page Start: 1
• Page End: 16
• Publication Date: 2017-08
• Subjects: Beta regression tree -- Customer retention -- Container shipping industry; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2017.04.015
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: The beta regression tree is used to segment and describe the container shipping market. The market is segmented into five segments in terms of likelihood of customer retention for the industry (LNC). Service quality is the only attribute which separates customer market into five group. The attributes of price and discount, personal selling and customer relationship have significant impact on LNC. Satisfactory personal selling is the most important attribute for increasing LNC. Abstract: This study segments container shipping market by analyzing the relationships between service attributes and likelihood of customer retention for the container shipping industry and find: (1) service quality, as a partitioned variable, separates the overall model into five sub-models having different functional relationships, (2) the attributes of price and discount, personal selling and customer relationship have significant impact on likelihood of customer retention, (3) satisfactory price and discounts are a necessary attribute to support the likelihood of customer retention, and (4) satisfactory personal selling is the most important attribute for increasing the likelihood of customer retention.