Towards machine learning for moral choice analysis in health economics: A literature review and research agenda

Background: Discrete choice models (DCMs) for moral choice analysis will likely lead to erroneous model outcomes and misguided policy recommendations, as only some characteristics of moral decision-making are considered. Machine learning (ML) is recently gaining interest in the field of discrete choice modelling. This paper explores the...

Moral rhetoric in discrete choice models: a Natural Language Processing approach

This paper proposes a new method to combine choice- and text data to infer moral motivations from people’s actions. To do this, we rely on moral rhetoric, in other words, extracting moral values from verbal expressions with Natural Language Processing techniques. We use moral rhetoric based on a well-established moral, psychological theory...

Secure or usable computers? Revealing employees’ perceptions and trade-offs by means of a discrete choice experiment

It is often suggested in the literature that employees regard technical security measures (TSMs) as user-unfriendly, indicating a trade-off between security and usability. However, there is little empirical evidence of such a trade-off, nor about the strength of the associated negative correlation and the importance employees attach to both...