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Guerreiro, J., Rita, P. & Trigueiros, D. (2016). A text mining-based review of cause-related marketing literature. Journal of Business Ethics. 139 (1), 111-128

J. R. Guerreiro et al.,  "A text mining-based review of cause-related marketing literature", in Journal of Business Ethics, vol. 139, no. 1, pp. 111-128, 2016

@article{guerreiro2016_1734975995973,
	author = "Guerreiro, J. and Rita, P. and Trigueiros, D.",
	title = "A text mining-based review of cause-related marketing literature",
	journal = "Journal of Business Ethics",
	year = "2016",
	volume = "139",
	number = "1",
	doi = "10.1007/s10551-015-2622-4",
	pages = "111-128",
	url = "http://link.springer.com/article/10.1007/s10551-015-2622-4"
}

TY  - JOUR
TI  - A text mining-based review of cause-related marketing literature
T2  - Journal of Business Ethics
VL  - 139
IS  - 1
AU  - Guerreiro, J.
AU  - Rita, P.
AU  - Trigueiros, D.
PY  - 2016
SP  - 111-128
SN  - 0167-4544
DO  - 10.1007/s10551-015-2622-4
UR  - http://link.springer.com/article/10.1007/s10551-015-2622-4
AB  - Cause-related marketing (C-RM) has risen to become a popular strategy to increase business value through profit-motivated giving. Despite the growing number of articles published in the last decade, no comprehensive analysis of the most discussed constructs of cause-related marketing is available. This paper uses an advanced Text Mining methodology (a Bayesian contextual analysis algorithm known as Correlated Topic Model, CTM) to conduct a comprehensive analysis of 246 articles published in 40 different journals between 1988 and 2013 on the subject of cause-related marketing. Text Mining also allows quantitative analyses to be performed on the literature. For instance, it is shown that the most prominent long-term topics discussed since 1988 on the subject are “brand-cause fit”, “law and Ethics”, and “corporate and social identification”, while the most actively discussed topic presently is “sectors raising social taboos and moral debates”. The paper has two goals: first, it introduces the technique of CTM to the Marketing area, illustrating how Text Mining may guide, simplify, and enhance review processes while providing objective building blocks (topics) to be used in a review; second, it applies CTM to the C-RM field, uncovering and summarizing the most discussed topics. Mining text, however, is not aimed at replacing all subjective decisions that must be taken as part of literature review methodologies.
ER  -