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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Portela, S. & Menezes, R. (2010). Analysing the customer churn risk using duration models. Journal of Combinatorics, Information & System Sciences: A Quarterly International Scientific Journal. 35 (1-2), 203-220
Exportar Referência (IEEE) 
S. M. Portela and R. M. Menezes,  "Analysing the customer churn risk using duration models", in Journal of Combinatorics, Information & System Sciences: A Quarterly Int. Scientific Journal, vol. 35, no. 1-2, pp. 203-220, 2010
Exportar BibTeX 
@article{portela2010_1715074119544,
	author = "Portela, S. and Menezes, R.",
	title = "Analysing the customer churn risk using duration models",
	journal = "Journal of Combinatorics, Information & System Sciences: A Quarterly International Scientific Journal",
	year = "2010",
	volume = "35",
	number = "1-2",
	pages = "203-220",
	url = "https://www.printspublications.com/journal/journalofcombinatoricsinformationsystemsciencesaquarterlyinternationalscientificjournal16632080702246932604"
}
Exportar RIS 
TY  - JOUR
TI  - Analysing the customer churn risk using duration models
T2  - Journal of Combinatorics, Information & System Sciences: A Quarterly International Scientific Journal
VL  - 35
IS  - 1-2
AU  - Portela, S.
AU  - Menezes, R.
PY  - 2010
SP  - 203-220
SN  - 0250-9628
UR  - https://www.printspublications.com/journal/journalofcombinatoricsinformationsystemsciencesaquarterlyinternationalscientificjournal16632080702246932604
AB  - Customer churn is the customer’s decision to terminate the relationship with a provider. This decision can be very onerous to the business financial performance. As such, an a priori knowledge about the probability (risk) of a given customer to cancel the relationship with the firm in the next period is a valuable tool that allows firms to take preventive measures to avoid the defection of potentially profitable customers. This study aims to understand and predict customer lifetime in a contractual setting in order to improve the practice of customer portfolio management. A duration model is developed to understand and predict the residential customer churn in the fixed telecommunications industry in Portugal. The model is developed by using large-scale data from an internal database of a Portuguese company which presents bundled offers of ADSL, fixed line telephone, pay-TV and home-video. The model is estimated with a large number of covariates, which includes customer’s basic information, demographics, churn flag, customer historical information about usage, billing, subscription, credit, and other
ER  -