Valence Framing in Multi-attribute Decision-making

This dataset contains responses from an online discrete choice experiment (DCE) designed to examine the effects of valence framing in a multi-attribute decision-making context. Three types of framing were manipulated across different attributes: risky-choice framing (gain vs. loss) was applied to the seat availability attribute, where options were described in terms of either seats free or seats taken; attribute framing (positive vs. negative) was applied to the service quality attribute, with descriptions highlighting either customer satisfaction or dissatisfaction levels; and goal framing (gain vs. loss) was applied to the CO₂ emissions attribute, emphasising either relative emissions saved or missed out on being saved. In each choice task, respondents selected their preferred alternative from two trains defined by these attributes and travel time and cost. The dataset also includes task completion timestamps, demographic information including age, gender, income, and the order in which each respondent completed the choice tasks, as well as self-reported risk preference.