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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) 
Lopes, R. R., Navarro, J. & Silva, A. J. (2018). Emotions as proximal causes of word of mouth: a nonlinear approach. Nonlinear Dynamis, Psychology, and Life Sciences. 22 (1), 103-125
Exportar Referência (IEEE) 
R. Rueff-Lopes et al.,  "Emotions as proximal causes of word of mouth: a nonlinear approach", in Nonlinear Dynamis, Psychology, and Life Sciences, vol. 22, no. 1, pp. 103-125, 2018
Exportar BibTeX 
@article{rueff-lopes2018_1714278128408,
	author = "Lopes, R. R. and Navarro, J. and Silva, A. J.",
	title = "Emotions as proximal causes of word of mouth: a nonlinear approach",
	journal = "Nonlinear Dynamis, Psychology, and Life Sciences",
	year = "2018",
	volume = "22",
	number = "1",
	pages = "103-125",
	url = "http://www.societyforchaostheory.org/ndpls/"
}
Exportar RIS 
TY  - JOUR
TI  - Emotions as proximal causes of word of mouth: a nonlinear approach
T2  - Nonlinear Dynamis, Psychology, and Life Sciences
VL  - 22
IS  - 1
AU  - Lopes, R. R.
AU  - Navarro, J.
AU  - Silva, A. J.
PY  - 2018
SP  - 103-125
SN  - 1090-0578
UR  - http://www.societyforchaostheory.org/ndpls/
AB  - Service research tends to operationalize word of mouth (WOM) behavior as one of the many responses to service satisfaction. In this sense, little is known about its antecedents or moderators. The objective of this study was to investigate the role of customers’ emotions during service experiences on WOM, applying nonlinear techniques and exploring the moderating role of customers’ propensity for emotional contagion. Using the critical incidents technique, 122 customers recalled significant service experiences and the emotions they aroused, and reported if they shared said experiences with other individuals. We found that, whereas linear methods presented non-significant results in the emotions-WOM relationship, nonlinear ones (artificial neural networks) explained 46% of variance. Negative emotions were stronger predictors of WOM and the importance of emotions for WOM was significantly higher for individuals with high propensity for emotional contagion (R^2 = .79) than for those with lower levels (R^2 = .48). Theoretical and practical implications are discussed.
ER  -