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 (R 2Turnover = .51, p < .01; R 2Cardiovascular efficiency = .32, p < .01). The importance of results for theory and practice is discussed.