When choosing, people often anticipate how they might feel about future outcomes, and use those feelings as guides to choices. Although the impact of emotions on decision-making is well-documented, both theoretically and empirically, relatively limited efforts have been made to quantitatively incorporate such anticipated emotions, specifically regret, into the discrete choice model, which is a workhorse for investigating various consumer choices in marketing. Regret theory suggests that the most relevant emotion in the context of decision-making is regret, which is the emotion that we experience when realizing or imagining that our current situation would have been better, if only we had decided differently. Consumers are known to be regret-averse and motivated to avoid regret. What is unique about regret is that it is directly linked to the choice or decision at hand, while other emotions relevant to decision-making may occur in the absence of a decision because these emotions are related to aspects of outcomes or uncertainty. In transportation science, a new econometric, multinomial, multi-attribute reference-dependent discrete choice model of random regret minimization (RRM) based on regret theory has recently been proposed. In this paradigm, individuals are assumed to make decisions so as to minimize the anticipated regret, which is experienced when a foregone alternative performs better than the chosen alternative at attribute-levels. However, there have been limited efforts to utilize the RRM to investigate consumers’ choices although marketing has long been interested in understanding consumers’ choices. Furthermore, despite the growing interest in the RRM in other disciplines, relatively little is known about the potential drivers for the decision rules of utility-maximization and regret-minimization. In this research, we attempt to shed light on a potential consumer-specific driver for decision rules between random utility maximization and random regret minimization in discrete choice modeling to gain a better understanding of consumers’ decision process, while introducing the RRM in the marketing domain. Specifically, we investigate what types of consumers are more likely to be regret-minimizers or utility-maximizers based on regulatory focus theory. We posit that chronically prevention-focused consumers are more likely to be regret-minimizers while chronically promotion-focused consumers are more likely to be utility-maximizers. We employ a latent class modeling framework to incorporate structural heterogeneity of decision rules to test the hypotheses using a discrete choice experiment on US residents. Notably, while the hypotheses are supported, a portion of prevention-focused consumers are in fact more likely to be utility-maximizers rather than regret-minimizers, indicating that the consumers’ regulatory focus is not entirely mapped with the decision rules on a one-to-one basis. The empirical finding further suggests that consumer-specific variables other than consumers’ chronic regulatory focus may be useful for identifying a regret-minimizing segment.

Measure noun phrases (MP), canonically realized in the form of X of Y, display such grammatical complexities that they challenge both theoretical linguists as well as even advanced EFL learners. MPs individuate and give classificatory information about Y, but induces grammatical indeterminacy with respect to number concord, selectional restriction, and modification patterns. This paper investigates the uses of MPs in the English corpus COCA and secondary-level English textbooks in Korea to shed light on the direction of better understanding of their properties both in theoretical and EFL contexts.