Understanding customer preferences in healthcare

: a conjoint analysis of private German health care add-ons

Abstract

Purpose - The insurance market is highly competitive, with insurers developing into a reliable partner for customers. Individualized and group-specific service catalogs are designed for this purpose. This work examines which add-ons are beneficial for which customer group. Design/Methodology - The study uses literature reviews and current trends to identify relevant add-ons for customer groups. A survey collects customer preference data to assign relative benefits of the add-ons to specific customer groups by using conjoint analysis and k-means clustering. Findings - The study shows that all selected add-ons do maximize benefits for some of the customer groups. However, this differs from one customer group to another and there is no single preferred add-on for all groups. Research limitations - The main limitation of this research is that conjoint analysis results cannot directly translate into consumer behavior. Additionally, survey data collection lacks precision, as add-ons and complex health insurance products cannot be detailed sufficiently. Practical implications - Health insurance companies can use this analysis to address customer groups in a more targeted manner. Social implications - Insurance companies can use the results to help target groups lead healthier lives with selected add-ons. Originality - To my knowledge, it is the only study that is focused on innovative add-ons in health care plans.

Date of Award	3 Jul 2024
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Fabio Caldieraro (Supervisor)