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Bas Donkers

Researcher at Erasmus University Rotterdam

Publications -  122
Citations -  5727

Bas Donkers is an academic researcher from Erasmus University Rotterdam. The author has contributed to research in topics: Discrete choice & Estimator. The author has an hindex of 32, co-authored 115 publications receiving 4709 citations. Previous affiliations of Bas Donkers include Queen's University Belfast & Erasmus Research Institute of Management.

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Undervalued or Overvalued Customers: Capturing Total Customer Engagement Value:

TL;DR: In this article, the authors propose four components of a customer's engagement value (CEV) with a firm: customer lifetime value (the customer's purchase behavior), customer referral value (as it relates to incentivized referral of new customers), customer influencer value (which includes the customer's behavior to influence other customers, that is increasing acquisition, retention, and share of wallet through word of mouth of existing customers as well as prospects).
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Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide

TL;DR: The purpose of this paper is to provide insight into whether and how researchers have dealt with sample size calculations for healthcare-related DCE studies, to introduce and explain the required sample size for parameter estimates in DCEs, and to provide a step-by-step guide for the calculation of the minimum sample size requirements for D CEs in health care.
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Estimating Risk Attitudes using Lotteries: A Large Sample Approach

TL;DR: In this paper, an index for risk aversion is estimated based on questions on lotteries in a large household survey and a structural model based on Cumulative Prospect Theory is proposed.
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The effect of acquisition channels on customer loyalty and cross-buying

TL;DR: In this paper, the authors explored how retention rates and cross-selling opportunities differ among the various acquisition channels a financial services provider uses and found that the direct-mail acquisition channel performs poorly on retention and cross selling, while radio and TV perform poorly for retention only.
Posted Content

Predicting Customer Potential Value: an application in the insurance industry

TL;DR: A model for predicting the potential value of a current customer is introduced and different modeling strategies for predicting this potential value are discussed and applied.