Objectives: Taboo trade-offs can explain some of the (moral) difficulties in healthcare decision-making. The moral psychology literature suggests that individuals are averse to making trade-offs between attributes belonging to different values, such as (sacred) human lives versus (secular) money. We demonstrate and empirically test a discrete choice model designed to capture Taboo Trade-off Aversion (TTOA) behaviors in the healthcare domain. Methods: The linear-additive Random Utility Maximization (RUM) model is extended to capture TTOA behaviors by including penalties for taboo trade-offs. Using two Discrete Choice Experiments (DCEs) focusing on taboo trade-offs in public health policies, we empirically compare conventional linear-additive RUM models with TTOA models to explore differences in model and behavioral results. Results: We observe TTOA in both DCEs. In one DCE, the TTOA model separates TTOA effects from attribute-related parameters, showing inflated parameters in conventional RUM models when TTOA behavior is present. This discrepancy affected Willingness-To-Pay (WTP) estimates, with WTP to save an incremental patient life approximately 3.5 times higher in conventional RUM models compared to the TTOA models. The presence and magnitude of TTOA varied considerably across respondents. Latent Class (LC) models reveal that some respondent groups perceive trade-offs as taboo significantly, while others do not. Conclusions: Accounting for TTOA in RUM models may lead to more accurate behavioral information when choice behaviors are affected by taboo trade-offs. Researchers and policymakers can use TTOA models to obtain a more nuanced understanding of public acceptability in morally salient policy decisions – ultimately helping to navigate, rather than avoid, taboo trade-offs.

This paper develops new directions on how individuals’ use of multiple goals can be incorporated in econometric models of individual decision-making. We start by outlining key components of multiple, simultaneous goal pursuit and multi-stage choice. Since different goals are often only partially compatible, such a multiple goal-based approach implies balancing goals, leading to a deliberate goal-level choice strategy on the part of the decision-maker. Accordingly, we introduce a conceptual framework to classify different aspects of individuals’ decisions in the presence of multiple goals. Based on this framework, we propose a formalization of individual decision-making when pursuing multiple goals. We briefly review different previous streams on goal-based decision-making and how the proposed goal-driven conceptual framework relates to earlier research in discrete choice models. The framework is illustrated using examples from different domains, in particular marketing, environmental economics, transportation, and sociology. Finally, we discuss identification and modeling needs for goal-based choice strategies and opportunities for further research.