In ten studies (N = 9187), I systematically investigated the direction and sizeof seven helping effects (the identifiable-victim effect, proportion dominanceeffect, ingroup effect, existence effect, innocence effect, age effect andgender effect). All effects were tested in three decision modes (separateevaluation, joint evaluation and forced choice), and in their weak form (equalefficiency), or strong form (unequal efficiency). Participants read about one,or two, medical help projects and rated the attractiveness of and allocatedresources to the project/projects, or choose which project to implement. Theresults show that the included help-situation attributes vary in their: (1)Evaluability – e.g., rescue proportion is the easiest to evaluate inseparate evaluation. (2) Justifiability – e.g., people prefer to savefewer lives now rather than more lives in the future, but not fewer identifiedlives rather than more statistical lives. (3) Prominence – e.g., peopleexpress a preference to help females, but only when forced to choose.

This paper illustrates how to apply the RECIPE design to evaluate multiattributejudgment, reporting an experiment in which participants judged intentions toreceive a new vaccine against COVID-19. The attributes varied were Price of thevaccine, Risks of side effects as reported in trials, and Effectiveness of thevaccine in preventing COVID. The RECIPE design is a union of factorial designsin which each of three attributes is presented alone, in pairs with each of theother attributes, and in a complete factorial with all other information.Consistent with previous research with analogous judgment tasks, the additiveand relative weight averaging models with constant weights could be rejected infavor of a configural weight averaging model in which the lowest-valuedattribute receives additional weight. That is, people are unlikely to acceptvaccination if Price is too high, Risk is too high, or Effectiveness is too low.The attribute with the greatest weight was Effectiveness, followed by Risk ofside-effects, and Price carried the least weight.

Previous research in multiple judgment domains has found that nonlinear functionsare typically processed less accurately than linear ones. This empiricalregularity has potential implications for consumer choice, given that nonlinearfunctions (e.g., diminishing returns) are commonplace. In two experimentalstudies we measured precision and bias in consumers’ ability to identifysurpluses when returns to product attributes were nonlinear. We hypothesizedthat nonlinear functions would reduce precision and induce bias towardlinearization of nonlinear relationships. Neither hypothesis was supported formonotonic nonlinearities. However, precision was greatly reduced for productswith nonmonotonic attributes. Moreover, assessments of surplus weresystematically and strongly biased, regardless of the shape of returns anddespite feedback and incentives. The findings imply that consumers use aflexible but coarse mechanism to compare attributes against prices, withimplications for the prevalence of costly mistakes.

Recent work has derived the optimal policy for two-alternative value-baseddecisions, in which decision-makers compare the subjective expected reward oftwo alternatives. Under specific task assumptions — such as linearutility, linear cost of time and constant processing noise — the optimalpolicy is implemented by a diffusion process in which parallel decisionthresholds collapse over time as a function of prior knowledge about averagereward across trials. This policy predicts that the decision dynamics of eachtrial are dominated by the difference in value between alternatives and areinsensitive to the magnitude of the alternatives (i.e., their summed values).This prediction clashes with empirical evidence showing magnitude-sensitivityeven in the case of equal alternatives, and with ecologically plausible accountsof decision making. Previous work has shown that relaxing assumptions aboutlinear utility or linear time cost can give rise to optimal magnitude-sensitivepolicies. Here we question the assumption of constant processing noise, infavour of input-dependent noise. The neurally plausible assumption ofinput-dependent noise during evidence accumulation has received strong supportfrom previous experimental and modelling work. We show that includinginput-dependent noise in the evidence accumulation process results in amagnitude-sensitive optimal policy for value-based decision-making, even in thecase of a linear utility function and a linear cost of time, for both single(i.e., isolated) choices and sequences of choices in which decision-makersmaximise reward rate. Compared to explanations that rely on non-linear utilityfunctions and/or non-linear cost of time, our proposed account ofmagnitude-sensitive optimal decision-making provides a parsimonious explanationthat bridges the gap between various task assumptions and between various typesof decision making.

Due to the information overload in today’s digital age, people maysometimes feel pressured to process and judge information especially fast. Inthree experiments, we examined whether time pressure increases therepetition-based truth effect — the tendency to judge repeatedlyencountered statements more likely as “true” than novelstatements. Based on the Heuristic-Systematic Model, a dual-process model in thefield of persuasion research, we expected that time pressure would boost thetruth effect by increasing reliance on processing fluency as a presumablyheuristic cue for truth, and by decreasing knowledge retrieval as a presumablyslow and systematic process that determines truth judgments. However, contraryto our expectation, time pressure did not moderate the truth effect.Importantly, this was the case for difficult statements, for which most peoplelack prior knowledge, as well as for easy statements, for which most people holdrelevant knowledge. Overall, the findings clearly speak against the conceptionof fast, fluency-based truth judgments versus slow, knowledge-based truthjudgments. In contrast, the results are compatible with a referential theory ofthe truth effect that does not distinguish between different types of truthjudgments. Instead, it assumes that truth judgments rely on the coherence oflocalized networks in people’s semantic memory, formed by both repetitionand prior knowledge.

The strategy method is a powerful method for eliciting conditional cooperation instrategic interactions. Theoretically, players’ cooperation conditionalon a specific level of others’ cooperation using the strategy methodshould be equal to their unconditional cooperation given an equivalent beliefabout others’ cooperation. However, using the Prisoner’s Dilemma,we show that decisions using the strategy method are more selfish than decisionsunder a simultaneous decision protocol predicted from players’ beliefs.This is driven entirely by lower cooperation among conditional cooperators withlow expectations about others’ cooperation. We further show that relativeto simultaneous choice, the strategy method shifts salient norms from anegalitarian fairness norm (‘give half’) to a reciprocity norm(‘match others’ behaviour’). This undermines cooperationamong players with low beliefs about others’ cooperation. These resultsthus show that the strategy method does not merely hold beliefs constant, butalso shifts which salient norms influence choice behaviour. This has importantimplications for the use of the strategy method in eliciting socialpreferences.

Measuring risk preferences using monetary incentives is costly. In the field, it might be also unfair and unsafe. The commonly used measure of Holt and Laury (2002) relies on a dozen lottery choices and payments, which make it time consuming and expensive. It also raises moral concerns as a result of the unequal payments generated by good and bad luck. Paying some but not all subjects may also create tensions between the researcher and subjects. In a pre-registered study in Honduras, Nigeria and Spain, we use a short version of Holt and Laury where we address all three concerns. We find in the field that not paying at all or paying with and without probabilistic rules makes no difference. Our hypothetical and short version makes our measurement of risk cheaper, fairer and safer.

In classic research on judgment and decision making under risk, risk is described by providing participants with the respective outcomes and probabilities in a summary format. Recent research has introduced a different paradigm – decisions-by-experience – where participants learn about risk by sampling from the outcomes, rather than by summary descriptions. This latter research reports a description-experience gap, indicating that some of the classic patterns of risk attitude reverse when people experience the risk. Recent research has attempted to investigate risky choice framing in the decisions-by-experience paradigm. I discuss how this research runs into problems in properly manipulating framing in decisions by experience. Drawing from framing research with animals, I argue that framing effects also exist in experience tasks. The classic Asian Disease task, however, awaits proper translation into an experience paradigm.