This paper presents a model of the effects of recovery level in terms of distributive, procedural, and interactional dimensions on consumer attitudes (satisfaction and trust) and their subsequent effects on behavioral intentions. Service medium (online and offline) is considered as a moderating variable in the perspective of psychological distance. Findings reveal that the effects of recovery levels on satisfaction and trust are greater in the offline medium than in the online medium. Moreover, in both low and high recovery situations, offline customers are more satisfied and have higher levels of trust than do online customers. As expected, satisfaction with service recovery plays a pivotal role in enhancing customer's trust and behavioral intentions.

Tests an hypothesized model which measures the overall satisfaction gained from, and the full spectrum of services attached to, the use of automated teller machines (ATMs). Sees overall satisfaction as the end result of a combined number of antecedents. Uses a LISREL model to test the structural effects of a number of exogenous variables (i.e. expectations and perceived risk) on a number of latent variables (desires congruency, self‐congruity, perceptions of relative influence and behavioural intentions) to a number of endogenous variables (satisfaction, recommendations to others, full use of services and the frequency of use). Overall, establishes a number of important structural links within the model which suggest that if banks wish to increase customers’ overall satisfaction and the usage of available services they must target factors which directly affect customers’ expectations and perceived risk.

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Self-reported measures are widely used to measure consumers' emotional responses to advertising stimuli or consumption-related experiences, and are a consistently popular method for practitioners and researchers. There is, however, a problem known as Bcognitive bias^which often arises from self-reported measures. Consequently, several researchers highlight the demand for the measurement of emotion to go beyond self-reported measures, and call for collaboration with other research fields to advance consumer behavior research in the study of emotion. This research collaborates with researchers in the field of human-computer interaction and suggests an alternative method: the Voice Emotion Response in Mandarin Chinese, which is one of the most widely spoken languages in the world. The findings show that the Voice Emotion Response, as compared to self-report, is more strongly related to recall. Preliminary outcomes reveal that this approach can potentially enhance the effectiveness of measuring emotions.