Empathy concerns enhance prosociality and modulate frontal theta oscillatory activity in young adults

Decision making is a process that can be strongly affected by social factors. Profuse evidence has shown how people deviate from traditional rational-choice predictions under different levels of social interactions. The emergence of prosocial decision making, defined as any action that is addressed to benefit another individual even at the expense of personal benefits, has been reported as an important example of such social influence. Furthermore, brain evidence has shown the involvement of structures such the prefrontal cortex, anterior insula and midcingulate cortex during decision settings in which a decision maker interacts with others under physical pain or distress or while being observed by others. Using a slightly modified version of the dictator game, we tested the hypothesis that the inclusion of another person into the decision setting increases prosocial decisions in young adults and that this increase is higher when the other person is associated with others in need. At the brain level, we hypothesized that the increase in prosocial decisions correlates with frontal theta activity as a marker of empathy saliency. The results showed that the inclusion of another person into the decision setting increased prosocial behavior only when this presence was associated with someone in need and that this was associated with an increase in frontocentral theta-oscillatory activity. These results suggest that the presence of someone in need enhances both empathy concerns and norm compliance, raising the participants’ prosocial decision making.

Competitive Agents in Certain and Uncertain Markets

This book uses concepts from optimization theory to develop an integrated analytic framework for treating consumer, producer, and market equilibrium analyses as special cases of a generic optimization problem. The same framework applies to both stochastic and non-stochastic decision settings, so that the latter is recognized as an (important) special case of the former. The analytic techniques are borrowed from convex analysis and variational analysis. Special emphasis is given to generalized notions of differentiability, conjugacy theory, and Fenchel's Duality Theorem. The book shows how virtually identical conjugate analyses form the basis for modeling economic behavior in each of the areas studied. The basic analytic concepts are borrowed from convex analysis. Special emphasis is given to generalized notions of differentiability, conjugacy theory, and Fenchel's Duality Theorem. It is demonstrated how virtually identical conjugate analyses form the basis for modelling economic behaviour in each of the areas studied.

Preference Dynamics in Sequential Consumer Choice with Defaults

This research examines the impact of defaults on product choice in sequential-decision settings. Whereas prior research has shown that a default can affect what consumers purchase by promoting choice of the preselected option, the influence of defaults is more nuanced when consumers make a series of related choices. In such a setting, consumer preferences may evolve across choices due to “spillover” effects from one choice to subsequent choices. The authors hypothesize that defaults systematically attenuate choice spillover effects because accepting a default is a more passive process than either choosing a nondefault option in the presence of a default or making a choice in the absence of a default. Three experiments and a field study provide compelling evidence for such default-induced changes in choice spillover effects. The findings show that firms’ setting of high-price defaults with the aim of influencing consumers to choose more expensive products can backfire through the attenuation of spillover. In addition to advancing the understanding of the interplay between defaults and preference dynamics, insights from this research have important practical implications for firms applying defaults in sequential choices.

Prosocial Preferences Condition Decision Effort and Ingroup Biased Generosity in Intergroup Decision-Making

Ingroup favoritism and discrimination against outgroups are pervasive in socialinteractions. To uncover the cognitive processes underlying generosity towards in- and out-group members, we employ eye-tracking in two pre-registered studies. We replicate the well- established ingroup favoritism effect and uncover that in-group compared to out-group decision settings are characterized by systematic differences in information search effort (i.e., increased response times and number of fixations, more inspected information) and attention distribution. Surprisingly, these results showed a stronger dependency on the in- vs. outgroup setting for more individualistic compared to prosocial participants: Whereas individualistic decision makers invested relatively less effort into information search when decisions involved out-group members, prosocial decision makers’ effort differed less between in- and outgroup decisions. Therein, choice and processing findings showed some interesting differences, indicating that inferences about the decision process from choices alone can be misleading. Implications for intergroup research and the regulation of intergroup conflict are discussed.

Impact of Context Information on Metaphor Elaboration

In experiments by Gibbs, Kushner, and Mills (1991) , sentences were supposedly either authored by poets or by a computer. Gibbs et al. (1991) concluded from their results that the assumed source of the text influences speed of processing, with a higher speed for metaphorical sentences in the Poet condition. However, the dependent variables used (e.g., mean RTs) do not allow clear conclusions regarding processing speed. It is also possible that participants had prior biases before the presentation of the stimuli. We conducted a conceptual replication and applied the diffusion model ( Ratcliff, 1978 ) to disentangle a possible effect on processing speed from a prior bias. Our results are in accordance with the interpretation by Gibbs et al. (1991) : The context information affected processing speed, not a priori decision settings. Additionally, analyses of model fit revealed that the diffusion model provided a good account of the data of this complex verbal task.

Is commercial lending affected by knowledge of auditor switches from Big 4 firms to regional firms?

Purpose This paper aims to examine whether knowledge about companies switching auditors from Big 4 firms to regional firms affects commercial lending decisions. Design/methodology/approach The approach used is an experiment where bank loan officers make judgments about risk and probabilities of granting a line of credit. Findings Neither risk assessments nor probabilities of granting credit differed for companies that switch auditors from Big 4 firms to regional firms as compared to companies that did not switch auditors. For companies that did switch auditors, providing a reason for the switch did not influence lending decisions. Research limitations/implications Lenders were given questionnaires that do not contain all of the information they may have used in actual loan decision settings. Also, the hypothetical nature of the decisions and incentives may not produce the responses that would be given in actual lending scenarios. Practical implications When applying for bank loans, companies need not be concerned about having switched auditors from Big 4 to regional firms. Also, companies that switch from Big 4 firms to regional firms need not worry about whether or not to provide a reason for the audit firm switch. Originality value This study adds to the auditor switching literature by investigating the effects of switches from Big 4 firms to regional firms on commercial lending decisions.

Can you moderate an unreadable message? 'Blind' content moderation via human computation

User-generated content (UGC) is fundamental to online social engagement, but eliciting and managing it come with many challenges. The special features of UGC moderation highlight many of the general challenges of human computation in general. They also emphasize how moderation and privacy interact: people have rights to both privacy and safety online, but it is difficult to provide one without violating the other: scanning a user's inbox for potentially malicious messages seems to imply access to all safe ones as well. Are privacy and safety opposed, or is it possible in some circumstance to guarantee the safety of anonymous content without access to that content. We demonstrate that such "blind content moderation" is possible in certain domains. Additionally, the methods we introduce offer safety guarantees, an expressive content space, and require no human moderation load: they are safe, expressive, and scalable Though it may seem preposterous to try moderating UGC without human- or machine-level access to it, human computation makes blind moderation possible. We establish this existence claim by defining two very different human computational methods, behavioral thresholding and reverse correlation. Each leverages the statistical and behavioral properties of so-called "inappropriate content" in different decision settings to moderate UGC without access to a message's meaning or intention. The first, behavioral thresholding, is shown to generalize the well-known ESP game.