A deeper understanding of pedestrian dynamics is essential to improve crowd flows in public spaces such as train stations. It is essential to understand both the physical and the psychological processes present in this context. However, current research on train boarding behavior is limited in scope and mainly focuses on how group level variables such as number of boarders/deboarders influence train boarding efficiency. Viewing pedestrian dynamics through a psychological lens is important for a detailed understanding of the train boarding context and to recognize target areas for improvement. At Dutch train stations, boarders follow a social norm of waiting at the train door until deboarding is complete. Although people generally adhere to this norm, the way it is executed may not be optimal for deboarding efficiency. We investigate how waiting boarders form a deboarding channel (a corridor where deboarders exit the train) and how this channel in turn influences the efficiency of deboarding. Analyzing a dataset with 3278 boarding events at Utrecht Centraal Station in the Netherlands from 2017 to 2020 (subset of a trajectory dataset capturing 100,000 trajectories per day), we found that higher numbers of boarders and a higher ratio of boarders to deboarders, reduced the width of the deboarding channel, and a lower width was associated with lower deboarding efficiency. These results shift the focus from group level variables to identifying macroscopic structures that are formed when pedestrians interact within a social system and provide specific target areas where nudges/behavioral interventions could be implemented.

Current research on the train boarding process focuses predominantly on the physical modelling of pedestrian dynamics and situational characteristics such as platform design. Little psychology is involved in this approach even though individual behavior is a major factor in influencing dwell times. We take a systematic psychological approach to estimate whether parameters like pedes-train speed, area available per pedestrian, and interpersonal distance show variation at the microscopic level (individual variation), macroscopic level (situational variation), or both. Analyzing real-life train (de)boarding events (n = 3728) at a specific location at a Dutch train station, we find that boarders’ speed varies more at the microscopic (individual variation) than the macroscopic level. This behavior could thus result from stable aspects of the situation such as some structural feature of the environment or a social norm. Understanding such variation is help-ful in designing behavioral interventions/nudges. If variation is due to individual differences, then an individual-targeted intervention will be most effective. If variation is due to situational differences, then individual-targeted interventions may not be particularly useful, and nudges targeted at crowds or environmental features may be most effective.

Many apps (e.g., social media, online streaming) include a social component where individual privacy decisions go beyond individual contexts and affect other people. We investigated people's willingness to adopt four apps and assessed the attentional processes underlying how people make tradeoffs when their own privacy and/or others' privacy is violated in a within-subjects design (NStudy1 = 304; NStudy2 = 355). We also assessed individual differences in the willingness to adopt apps in terms of other-oriented traits (e.g., empathic concern, justice sensitivity etc.). The main findings show that (1) when own privacy was protected and others' privacy was not protected, people were more willing to adopt apps (compared to when others' privacy was protected and own privacy not protected). (2) Individual differences in information acquisition predicted the decision to adopt apps. More attention to others' privacy information was associated with lower willingness to adopt apps when others' privacy was not protected. (3) Higher sensitivity to justice and self-transcendence values were associated with lower adoption of the apps when self or other-privacy violations were present. Our results suggest that people differ in how much they care about whether their privacy decisions might affect others negatively. Accordingly, they differ in their attention to privacy information especially in situations where own and others' privacy is in conflict. People's justice concerns extend to concern for both self and other-privacy violations. These findings imply that although people may care about privacy, individual differences are important to understand why people care about own and others' privacy differently.

According to cognitive-dissonance theory, performing counterattitudinal behavior produces a state of dissonance that people are motivated to resolve, usually by changing their attitude to be in line with their behavior. One of the most popular experimental paradigms used to produce such attitude change is the induced-compliance paradigm. Despite its popularity, the replication crisis in social psychology and other fields, as well as methodological limitations associated with the paradigm, raise concerns about the robustness of classic studies in this literature. We therefore conducted a multilab constructive replication of the induced-compliance paradigm based on Croyle and Cooper (Experiment 1). In a total of 39 labs from 19 countries and 14 languages, participants (N = 4,898) were assigned to one of three conditions: writing a counterattitudinal essay under high choice, writing a counterattitudinal essay under low choice, or writing a neutral essay under high choice. The primary analyses failed to support the core hypothesis: No significant difference in attitude was observed after writing a counterattitudinal essay under high choice compared with low choice. However, we did observe a significant difference in attitude after writing a counterattitudinal essay compared with writing a neutral essay. Secondary analyses revealed the pattern of results to be robust to data exclusions, lab variability, and attitude assessment. Additional exploratory analyses were conducted to test predictions from cognitive-dissonance theory. Overall, the results call into question whether the induced-compliance paradigm provides robust evidence for cognitive dissonance.

Nudging has become a popular method to change the behavior of pedestrians in public spaces. However, nudges often do not work as intended because they are based on an incomplete understanding of the nudging environment, physical (e.g., pedestrian trajectories), but not psychological data is used in their development, and behavioral theories are often inadequate or not (correctly) applied. In this article, we argue that the design of nudges can benefit from complementary psychological data analyzed using relevant social and environmental psychological theories. Adequate theories, we argue, are those that aim at describing the objective (i.e., person independent) attributes of the environment or situation and how these affect human decision-making. Using the example of train boarding, and in particular the formation of the deboarding corridor, we demonstrate how psychological theories like interdependence theory and social norms theory can be applied to relevant psychological data—in our case obtained with two focus groups—to better characterize the sociophysical attributes of the train boarding situation. The focus group, or sometimes called a “group discussion”, is a qualitative research method in which data is generated from guided discussions amongst research participants following pre-defined discussion topics. Based on the thematic analysis of the focus group data, we find that a high level of competition and interdependence are related to structural aspects of the train boarding situation. Subsequently, we use these insights to provide tentative explanations for, or hypotheses about micro- and macroscopic behavior patterns observed during train boarding. Finally, we discuss how these insights, in turn, can inform the design of nudges that can be further investigated in future research.

Moral framing and reframing strategies persuade people holding moralized attitudes (i.e., attitudes having a moral basis). However, these strategies may have unintended side effects: They have the potential to moralize people's attitudes further and as a consequence lower their willingness to compromise on issues. Across three experimental studies with adult U.S. participants (Study 1: N = 2,151, Study 2: N = 1,590, Study 3: N = 1,015), we used persuasion messages (moral, nonmoral, and control) that opposed new big-data technologies (crime-surveillance technologies and hiring algorithms). We consistently found that moral frames were persuasive and moralized people's attitudes, whereas nonmoral frames were persuasive and de-moralized people's attitudes. Moral frames also lowered people's willingness to compromise and reduced behavioral indicators of compromise. Exploratory analyses suggest that feelings of anger and disgust may drive moralization, whereas perceiving the technologies to be financially costly may drive de-moralization. The findings imply that use of moral frames can increase and entrench moral divides rather than bridge them.

The study of moral judgements often centres on moral dilemmas in which options consistent with deontological perspectives (that is, emphasizing rules, individual rights and duties) are in conflict with options consistent with utilitarian judgements (that is, following the greater good based on consequences). Greene et al. (2009) showed that psychological and situational factors (for example, the intent of the agent or the presence of physical contact between the agent and the victim) can play an important role in moral dilemma judgements (for example, the trolley problem). Our knowledge is limited concerning both the universality of these effects outside the United States and the impact of culture on the situational and psychological factors affecting moral judgements. Thus, we empirically tested the universality of the effects of intent and personal force on moral dilemma judgements by replicating the experiments of Greene et al. in 45 countries from all inhabited continents. We found that personal force and its interaction with intention exert influence on moral judgements in the US and Western cultural clusters, replicating and expanding the original findings. Moreover, the personal force effect was present in all cultural clusters, suggesting it is culturally universal. The evidence for the cultural universality of the interaction effect was inconclusive in the Eastern and Southern cultural clusters (depending on exclusion criteria). We found no strong association between collectivism/individualism and moral dilemma judgements. Including participants from 45 countries, Bago et al. find that the situational factors that affect moral reasoning are shared across countries, with diminished observed cultural variation.

Theories of moralization argue that moral relevance varies due to inter-individual differences, domain differences, or a mix of both. Predictors associated with these sources of variation have been studied in isolation to assess their unique contribution to moralization. Across three studies (N-Study1 = 376; N-Study2a = 621; N-Study2b = 589), assessing attitudes towards new big data technologies, we found that moralization is best explained by theories focusing on inter-individual variation (similar to 29%) and intra-individual variation across technology domains (similar to 49%), and less by theories focusing on differences between technology domains (similar to 6%). We simultaneously examined 15 inter-individual and 16 intra-individual predictors that potentially explain this variation. Predictors directly relevant to the technologies (e.g., justice concerns), cognitive styles (e.g., faith in intuition), and emotional reactions (e.g., anger) best explain variation in moral relevance. Accordingly, scholars should simultaneously adopt and adapt moralization theories related to inter-individual and intra-individual differences across domains rather than in isolation.

Big data technologies have both benefits and costs which can influence their adoption and moral acceptability. Prior studies look at people's evaluations in isolation without pitting costs and benefits against each other. We address this limitation with a conjoint experiment (N = 979), using six domains (criminal investigations, crime prevention, citizen scores, healthcare, banking, and employment), where we simultaneously test the relative influence of four factors: the status quo, outcome favorability, data sharing, and data protection on decisions to adopt and perceptions of moral acceptability of the technologies. We present two key findings. (1) People adopt technologies more often when data is protected and when outcomes are favorable. They place equal or more importance on data protection in all domains except healthcare where outcome favorability has the strongest influence. (2) Data protection is the strongest driver of moral acceptability in all domains except healthcare, where the strongest driver is outcome favorability. Additionally, sharing data lowers preference for all technologies, but has a relatively smaller influence. People do not show a status quo bias in the adoption of technologies. When evaluating moral acceptability, people show a status quo bias but this is driven by the citizen scores domain. Differences across domains arise from differences in magnitude of the effects but the effects are in the same direction. Taken together, these results highlight that people are not always primarily driven by self-interest and do place importance on potential privacy violations. The results also challenge the assumption that people generally prefer the status quo.