Several studies have demonstrated the superior performance of ensemble classification algorithms, whereby multiple member classifiers are combined into one aggregated and powerful classification model, over single models. In this paper, two rotation-based ensemble classifiers are proposed as...

We investigate the issue of predicting new customers as profitable based on information about existing customers in a business-to-business environment. In particular, we show how latent semantic concepts from textual information of existing customers’ websites can be used to uncover...

Since charitable fundraising relies heavily on direct mail, this paper studies how tailoring donation requests along the donor lifecycle could improve campaign success rate. Our field study provides a unique combination of three parameters whose combined interaction has not been studied to this...

In this article, we develop a Bayesian method for quantile regression in the case of dichotomous response data. The frequentist approach to this type of regression has proven problematic in both optimizing the objective function and making inference on the regression parameters. By accepting...

Nowadays, an increasing number of information technology tools are implemented in order to support decision making about marketing strategies and improve customer relationship management (CRM). Consequently, an improvement in CRM can be obtained by enhancing the databases on which these...

spatial competition between stores of the same brand, brand attraction based on actual brand performance and spatially variable substitution. The model uses only publicly available or easily acquirable data as input, whereas model output is extensively validated on various levels. These levels...

This paper uses scanner data from two large retailers to offer new insights into the extent of price rigidity in Europe and the US. Recent empirical research in this field has made extensive use of monthly data to study price stickiness and to control for the impact of temporary sales. We show...

Past behavior and sociodemographics represent traditional predictors of charitable giving. The present study examines, in a real fundraising setting, whether measures of empathy (i.e., empathic concern and personal distress) can improve these predictions. The findings confirm the relevance of...

Using scanner data from a large European retailer, this paper empirically assesses deep habit formation in consumption. Deep habit formation constitutes a possible source of price stickiness and helps to mimic procyclical labour and real wage dynamics that are present in macro data. To gauge the...

This study investigates the advantage of social network mining in a customer retention context. A company that is able to identify likely churners in an early stage can take appropriate steps to prevent these potential churners from actually churning and subsequently increase profit. Academics...