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Rueff Lopes, M., Navarro, J., Caetano, A. & Junça Silva, A. (2017). Forecasting the influence of customer-related micro-events on employees’ emotional, attitudinal and physiological responses. European Journal of Work and Organizational Psychology. 26 (6), 779-797
M. R. Lopes et al., "Forecasting the influence of customer-related micro-events on employees’ emotional, attitudinal and physiological responses", in European Journal of Work and Organizational Psychology, vol. 26, no. 6, pp. 779-797, 2017
@article{lopes2017_1732201030835, author = "Rueff Lopes, M. and Navarro, J. and Caetano, A. and Junça Silva, A.", title = "Forecasting the influence of customer-related micro-events on employees’ emotional, attitudinal and physiological responses", journal = "European Journal of Work and Organizational Psychology", year = "2017", volume = "26", number = "6", doi = "10.1080/1359432X.2017.1360286", pages = "779-797", url = "http://www.tandfonline.com/doi/full/10.1080/1359432X.2017.1360286" }
TY - JOUR TI - Forecasting the influence of customer-related micro-events on employees’ emotional, attitudinal and physiological responses T2 - European Journal of Work and Organizational Psychology VL - 26 IS - 6 AU - Rueff Lopes, M. AU - Navarro, J. AU - Caetano, A. AU - Junça Silva, A. PY - 2017 SP - 779-797 SN - 1359-432X DO - 10.1080/1359432X.2017.1360286 UR - http://www.tandfonline.com/doi/full/10.1080/1359432X.2017.1360286 AB - The affective events theory proposes that daily events elicit affective reactions on workers that, over time, influence affective and judgement-driven behaviours. It also suggests that this relation is moderated by dispositions and appraisals. On the other hand, the social interaction model argues that the impact of emotions is moderated by how individuals regulate them. This study aimed to: (1) investigate what customer-related events elicit affect; (2) test the moderating role of workers’ susceptibility for emotional contagion on the relation events-affect; and (3) explore whether affective states influence cardiovascular efficiency and turnover intentions. We conducted a longitudinal study in an inbound call centre by following 48 workers during 10 working days, gathering 267 events and 1,232 affective reactions. We combined diaries, questionnaires and physiological data. Data was analysed qualitatively and quantitatively. We extracted 13 event categories and, using artificial neural networks (ANN), found support for the moderating role of emotional contagion. At daily level, fear was the stronger predictor of cardiovascular efficiency, whereas anger was the stronger predictor of turnover. ANN models showed satisfactory predictive values (R2Turnover = .51, p < .01; R2Cardiovascular efficiency = .32, p < .01). The importance of results for theory and practice is discussed. ER -