Veröffentlichungen von Laura Bayor

Machines such as AI companions, equipped with enhanced cognitive capabilities, can now be considered as an equal communicative subject that is capable of social communication. To take account of this, we will unfold what benefits and costs are associated with engaging in social communication with a machine. This research-in-progress paper employs a qualitative research design based on social exchange theory to give theoretical insights. We expect to contribute with this research by revealing the costs and benefits of social communication in the human-machine communication context, developing an understanding of how the cost-benefit calculation differs within the context of social communication between humans and machines, and contributing to the upcoming research stream on AI companions.

Although experiencing guilt feelings after social networking service (SNS) usage has become a prevalent phenomenon among SNS users, these SNS guilt feelings - and especially their causes - have received little scholarly attention. This paper therefore focuses on why SNS users may develop SNS guilt feelings and their impact on discontinuance intention. We utilize the lens of normative dissociation to develop a model to identify causes of SNS guilt feelings and apply a quantitative research approach to test the model. We contribute by demonstrating that two identified causes - perceived time spent and perceived procrastination – significantly influence SNS guilt feelings, while perceived meaningfulness does not. Furthermore, SNS guilt feelings influence discontinuance intention and mediate the relationship between several constructs and discontinuance intention. By employing the perspective of normative dissociation, we reinforce the relevance of SNS guilt feelings.

IS research increasingly recognizes that affective responses play an important role in explaining continuance intention. However, most research disregards the variety and complexity of affective responses. Encountering models with multiple affective responses included is scarce, and possible relationships among different affective responses are neglected. This paper develops a model measuring continuance intention in the context of fitness applications using three fundamentally different, but complementary affective responses: IS satisfaction, deep engagement, and meaningful engagement. An empirical investigation using an online survey is conducted. The findings demonstrate that different affective responses influence continuance intention in distinct ways, and that there are interrelations between affective responses. Deep engagement and IS satisfaction have a direct influence on continuance intention, and there is an indirect relationship between meaningful engagement and continuance intention mediated by IS satisfaction. Contributions to theory and practice are discussed.