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According to L. A. Paul ( 2014 ), transformative experiences pose a challenge for decision theory, as their subjective value is not epistemically accessible. However, several authors propose that the subjective values of options are often irrelevant to their ranking; in many cases, all we need for rational transformative decision-making are the known non-subjective values. This stance is in conflict with Paul’s argument that the subjective value can always swamp the non-subjective value. The approach presented in this paper takes Paul’s argument into account and shows how potential swamping can be controlled given that one desires the transformative outcome: If one knows from previous decisions that desired transformative outcomes are associated with positive subjective value and if, in addition, testimony confirms this association for the current decision situation, one can infer that a desired outcome’s expected subjective value has a positive valence. Accordingly, one can rationally choose the desired transformative option if its non-subjective value is no lower than the overall value of any other option.

Differences between academic disciplines have been a well-studied theme in higher education research. But even though students’ subjective study values are a key factor for successful studying, research examining their disciplinary differences in the higher education context is lacking. To address this, this study draws on expectancy-value theory, investigates students’ subjective study values across nine different disciplines, and analyses its discipline-specific relation to study success. For this, we used a large-scale data sample of N  = 6.321 university students from the German National Educational Panel Study. Subjective study values were assessed in terms of intrinsic values, utility values, attainment values, and costs, while study success was captured by students’ grade and dropout intention. Data were analysed through multi-group structural equation modelling. Our findings suggest that (1) students’ subjective study values differ markedly across academic disciplines and (2) study disciplines moderate the relation between study values and study success. On a research level, our findings contribute to a more differentiated view on subjective study values in the higher education context. On a practical level, our findings can help to uncover motivational problems of students from different disciplines, which might ultimately help to reduce dropouts and improve grades.

Mirror neurons are a specific type of visuomotor neuron that discharge both when a monkey executes a motor act and when it observes a similar motor act performed by another individual. In this article, we review first the basic properties of these neurons. We then describe visual features recently investigated which indicate that, besides encoding the goal of motor acts, mirror neurons are modulated by location in space of the observed motor acts, by the perspective from which the others’ motor acts are seen, and by the value associated with the object on which others’ motor acts are performed. In the last part of this article, we discuss the role of the mirror mechanism in planning actions and in understanding the intention underlying the others’ motor acts. We also review some human studies suggesting that motor intention in humans may rely, as in the monkey, on the mirror mechanism.

Does the way that individuals pay for a good or service influence the amount of connection they feel after the purchase has occurred? Employing a multi-method approach across four studies, individuals who pay using a relatively more painful form of payment (e.g., cash or check) increase their post-transaction connection to the product they purchased and/or the organization their purchase supports in comparison to those who pay with less painful forms of payment (e.g., debit or credit card). Specifically, individuals who pay with more painful forms of payment increase their emotional attachment to a product, decrease their commitment to nonchosen alternatives, are more likely to publicly signal their commitment to an organization, and are more likely to make a repeat transaction. Moreover, the form of payment influences post-transaction connection even when the objective monetary cost remains constant and when the psychological cost is indirect (i.e., donating someone else’s money). Increasing the psychological pain of payment appears to have beneficial consequences with respect to increasing downstream product and brand connection.

Motivation is key for performance in domains such as work, sport, and learning. Research has established that motivation and the willingness to invest effort generally increase as a function of reward. However, this view struggles to explain some empirical observations—for example, in the domain of sport, athletes sometimes appear to lose motivation when playing against weak opponents—this despite objective rewards being high. This and similar evidence highlight the role of subjective value in motivation and effort allocation. To capture this, here, we advance a novel theory and computational model where motivation and effort allocation arise from reference-based evaluation processes. Our proposal argues that motivation (and the ensuing willingness to exert effort) stems from subjective value, which in turns depends on one’s standards about performance and on the confidence about these standards. In a series of simulations, we show that the model explains puzzling motivational dynamics and associated feelings. Crucially, the model identifies realistic standards (i.e., those matching one’s own actual ability) as those more beneficial for motivation and performance. On this basis, the model establishes a normative solution to the problem of optimal allocation of effort, analogous to the optimal allocation of neural and computational resources as in efficient coding.

We produce a definition and argument for explicitly adopting value subjectivism in entrepreneurship research. While the field has progressively shifted toward subjectivism over the past decades, we remain saddled with positivist baggage in our theories’ definitions of key variables, including the concept of value. Although modern scholars readily admit that value is subjective, what is generally meant by this is that it is idiosyncratically determined. We argue that value is more appropriately defined, atop pure subjectivism, as an increase in subjective satisfaction or well-being. We develop and elaborate on this definition and explore its implications for entrepreneurship theory and policy.

On the basis of the seminal work of Kahneman and Tversky Econometrica, 47(2): 263–292 (1979), this research extends the boundaries of prospect theory in investigating determinants and temporal variation of risk-taking in entrepreneurial decisions, such as creating a new business organization or investing a risky business project. The two experimental studies (1) identify entrepreneurial risk-taking in the gain situation and find reversal of risk preference after a dynamic entrepreneurial learning process, indicating that the framing effect of prospect theory in explaining entrepreneurial risk-taking is conditional; (2) instead of weights, subjective judgment of the possibility of success of a risky project (subjective probability) consistently plays central moderating role in entrepreneurial decisions under uncertainty, and (3) the different effects of subjective probability in the two studies reveal that novice decision-makers are more value-driven, whereas experienced decision-makers, particularly under low probability conditions, tend to be more risk averse regardless of the value of a risky project perceived as long as they have a lack of confidence in eventual success.

•Effort-based decision-making is best described by a power discounting model.•Multivariate dmPFC patterns represent subjective value across tasks and datasets.•These effects may not be detectable by univariate fMRI analyses.•These findings extend the scope of the neural common currency theory. Decisions that require taking effort costs into account are ubiquitous in real life. The neural common currency theory hypothesizes that a particular neural network integrates different costs (e.g., risk) and rewards into a common scale to facilitate value comparison. Although there has been a surge of interest in the computational and neural basis of effort-related value integration, it is still under debate if effort-based decision-making relies on a domain-general valuation network as implicated in the neural common currency theory. Therefore, we comprehensively compared effort-based and risky decision-making using a combination of computational modeling, univariate and multivariate fMRI analyses, and data from two independent studies. We found that effort-based decision-making can be best described by a power discounting model that accounts for both the discounting rate and effort sensitivity. At the neural level, multivariate decoding analyses indicated that the neural patterns of the dorsomedial prefrontal cortex (dmPFC) represented subjective value across different decision-making tasks including either effort or risk costs, although univariate signals were more diverse. These findings suggest that multivariate dmPFC patterns play a critical role in computing subjective value in a task-independent manner and thus extend the scope of the neural common currency theory.

Although the future often seems intangible, we can make it more concrete by imagining prospective events. Here, using functional MRI, we demonstrate a mechanism by which the ventromedial prefrontal cortex supports such episodic simulations, and thereby contributes to affective foresight: This region supports processes that ( i ) integrate knowledge related to the elements that constitute an episode and ( ii ) represent the episode’s emergent affective quality. The ventromedial prefrontal cortex achieves such integration via interactions with distributed cortical regions that process the individual elements. Its activation then signals the affective quality of the ensuing episode, which goes beyond the combined affective quality of its constituting elements. The integrative process further augments long-term retention of the episode, making it available at later time points. This mechanism thus renders the future tangible, providing a basis for farsighted behavior. Significance Decisions concerning the future are often informed by past experiences. However, in a complex world, we frequently have to make choices for prospective scenarios that we haven’t yet encountered. The present study demonstrates a critical role for the ventromedial prefrontal cortex in simulating what it may feel like to experience such future events. We show that this region contributes to integrating knowledge related to the elements that constitute the episode (e.g., the episode’s location and protagonists). Its activation then indicates the episode’s emergent or overall anticipated affective quality. By this process, the ventromedial prefrontal cortex fundamentally supports our ability to predict possible future affective states, a mechanism that can be flexibly used to augment future oriented decisions.

Why do we sometimes opt for actions or items that we do not value the most? Under current neurocomputational theories, such preference reversals are typically interpreted in terms of errors that arise from the unreliable signaling of value to brain decision systems. But, an alternative explanation is that people may change their mind because they are reassessing the value of alternative options while pondering the decision. So, why do we carefully ponder some decisions, but not others? In this work, we derive a computational model of the metacognitive control of decisions or MCD. In brief, we assume that fast and automatic processes first provide initial (and largely uncertain) representations of options' values, yielding prior estimates of decision difficulty. These uncertain value representations are then refined by deploying cognitive (e.g., attentional, mnesic) resources, the allocation of which is controlled by an effort-confidence tradeoff. Importantly, the anticipated benefit of allocating resources varies in a decision-by-decision manner according to the prior estimate of decision difficulty. The ensuing MCD model predicts response time, subjective feeling of effort, choice confidence, changes of mind, as well as choice-induced preference change and certainty gain. We test these predictions in a systematic manner, using a dedicated behavioral paradigm. Our results provide a quantitative link between mental effort, choice confidence, and preference reversals, which could inform interpretations of related neuroimaging findings.