Decision support for real-time telemarketing operations through Bayesian network learning
Decision Support Systems - Special issue: knowledge discovery and its applications to business decision making
Knowledge management and data mining for marketing
Decision Support Systems - Knowledge management support of decision making
Customer-oriented catalog segmentation: effective solution approaches
Decision Support Systems
Expert Systems with Applications: An International Journal
Random Forests for multiclass classification: Random MultiNomial Logit
Expert Systems with Applications: An International Journal
Predicting going concern opinion with data mining
Decision Support Systems
Quantifying the indirect effects of a marketing contact
Expert Systems with Applications: An International Journal
New Frontiers in Applied Data Mining
Expert Systems with Applications: An International Journal
Journal of Intelligent Information Systems
Modeling partial customer churn: On the value of first product-category purchase sequences
Expert Systems with Applications: An International Journal
Distributed customer behavior prediction using multiplex data: A collaborative MK-SVM approach
Knowledge-Based Systems
Random multiclass classification: generalizing random forests to random MNL and random NB
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Technology classification with latent semantic indexing
Expert Systems with Applications: An International Journal
Evaluation of the Shopping Path to Distinguish Customers Using a RFID Dataset
International Journal of Organizational and Collective Intelligence
Protecting research and technology from espionage
Expert Systems with Applications: An International Journal
Weak signal identification with semantic web mining
Expert Systems with Applications: An International Journal
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The acquisition process of consumer durables is a 'sequence' of purchase events. Priority-pattern research exploits this 'sequential order' to describe a prototypical acquisition order for durables. This paper adds a predictive perspective to increase managerial relevance. Besides order information, the acquisition sequence also reveals precise timing between purchase events ('sequential duration') as examined in the literature on durable replacement and time-to-first acquisition. This paper bridges the gap between priority-pattern research and research on duration between durable acquisitions to improve the prediction of the product group the customer might acquire his next durable from, i.e. Next-Product-to-Buy (NPTB) model. We evaluate four multinomial-choice models incorporating: 1) general covariates, 2) general covariates and sequential order, 3) general covariates and sequential duration, and 4) general covariates, sequential order and duration. The results favor the model including general covariates and duration information (3). The high predictive value of sequential-duration information emphasizes the predictive power of duration as compared to order information.