Consumers frequently encounter a variety of products to choose from and, to simplify decisions, many opt to only consider a subset of potential products on offer—the consideration set. The current study proposes a selective sampling account of consideration set formation when faced with a large variety of complex products and examines its implications. Across five studies, participants formed consideration sets for a variety of bundled products. Converging evidence from behavior and computational modeling has revealed that participants likely use selective attention in forming consideration sets among complex products. Consequently, the likelihood of certain bundles being included in the consideration set over others is modulated by the distribution of values among the most or least important items in the bundle, as well as by the display format. The effect of selective attention on consideration set inclusion in turn contributes to a higher likelihood of choosing that product over a similar but novel option. We conclude that consumers faced with a large variety of complex products often reduce processing demands by discounting seemingly less-relevant information, which could lead to choice biases, whereby a product bundle is preferred because of the subset of information that has been selectively attended to.

Recent research from economics, psychology, cognitive science, computer science, and marketing is increasingly interested in the idea that people face cognitive costs when making decisions. Reviewing and synthesizing this research, we develop a framework of cognitive costs that organizes concepts along a temporal dimension and maps out when costs occur in the decision-making process and how they impact decisions. Our unifying framework broadens the scope of research on cognitive costs to a wider timeline of cognitive processing. We identify implications and recommendations emerging from our framework for intervening on behavior to tackle some of the most pressing issues of our day, from improving health and saving decisions to mitigating the consequences of climate change.

The ability to discover patterns or rules from our experiences is critical to science, engineering, and art. In this paper, we examine how much people's discovery of patterns can be incentivized by financial rewards. In particular, we investigate a classic category learning task for which the effect of financial incentives is unknown (Shepard et al., 1961). Across five experiments, we find no effect of incentive on rule discovery performance. However, in a sixth experiment requiring category recognition but not learning, we find a large effect of incentives on response time and small effect on task performance. Participants appear to apply more effort in valuable contexts, but the effort is disproportionate with the performance improvement. Taken together, the results suggest that performance in tasks which require novel inductive insights are relatively immune to financial incentives, while tasks that require rote perseverance of a fixed strategy are more malleable.

People's mental representation of expenditures is crucial to their budgeting. This article proposes that much like how they represent natural kinds (e.g., animals and plants), people represent expenditures in a hierarchical taxonomy. Seven studies, supported by six norming studies and three pilots, revealed that expenditures are represented hierarchically. We first recover people's mental representations using a successive pile-sort method that asks people to form hierarchies of categories with common expenditures (e.g., rent, dining out, etc.). The pile-sort reveals consensus in people's representations of expenditures and that these representations are relatively stable over time. Further, people's adjustment in their spending behavior can be predicted by the distance between items in their representation. Specifically, when people overspent on an item, they spontaneously adjust spending more on taxonomically closer items. We examine this spontaneous adjustment behavior using both laboratory studies and field data with 6.5 million grocery shopping trips over 12 years. The findings highlight the connection between mental representation and consumer behavior, and they emphasize the importance of studying concepts and categories in the context of consumption.

Large Language Models (LLMs) are being increasingly used in scientific research, be it to analyze data, generate synthetic data, or even to write scientific papers. This trend necessitates that journal reviewers are able to evaluate the quality of works that utilize LLMs. We provide reviewers of psychological research with a comprehensive guide on evaluating research that uses LLMs, examining their dual roles of automating data processing and simulating human data. Essential considerations for reviewers are highlighted, focusing on the evaluation of methodological rigor, the importance of replicability, and the validity of results when employing LLMs. We offer practical advice on assessing the appropriateness of LLM applications in submitted studies, emphasizing the need for transparency in methodological reporting and the challenges posed by the non-deterministic and continuously evolving nature of these models. By providing a framework for critical review, this guide aims to ensure high-quality, innovative research within the evolving landscape of psychological studies utilizing LLMs.

Growing consumer concerns about data privacy necessitate organizations to consider what kind of data usage is deemed acceptable. Failure to address this can harm brands and products. Our research comprises 14 studies (1 pretest, 4 main studies, 1 supplemental study, and 3 manipulation checks and 5 norming studies; Total N=7,559), examining factors that determine acceptability in data privacy situations. In our first study, we crowdsource common situations and dimensions surrounding data privacy related situations. Our second study examines how these dimensions impact acceptability across 60 situations. Our third study manipulates these dimensions to test causal relationships. Our fourth study looks at how our dimensions impact consumer intentions to switch to other products with better privacy protections. Organizational security efforts, appropriate consent procedures for data collection, and the degree to which data collected and used are permanently associated with a consumer or not impacted appropriateness most. Sentiment towards an organization and whether a company gave consumers an option to opt out of providing their data while using the service also impacted acceptability. Finally, consumers are most likely to switch products if those products fail to have good security or fail to gain adequate consent for their use and collection of data.

A large literature implicates time preference (i.e., how much an outcome retains value as it is delayed) as a predictor of a wide range of behaviors, because most behaviors involve sooner and delayed consequences. We aimed to provide the most comprehensive examination to date of how well laboratory-derived estimates of time preference relate to self-reports of 36 behaviors, ranging from retirement savings to flossing, in a test-rest design using a large sample (N = 1,308) and two waves of data collection separated by 4.5 months. Time preference is significantly-albeit modestly-associated with about half of the behaviors; this is true even when controlling for 15 other demographic variables and psychologically relevant scales. There is substantial variance in the strengths of associations that is not easily explained. Time preference's predictive validity falls in the middle of these 16 possible predictors. Finally, we ask time preference researchers (N = 55) to predict the variation in the relationship between time preference and behaviors, and although they are reasonably well-calibrated, these experts tend to overestimate the predictive power of time preference estimates. We discuss implications of invoking time preference as a predictor and/or determinant of behaviors with delayed consequences in light of our findings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

In this paper, we provide a framework for conceptualizing and identifying differences between anchors and targets (i.e., non-status quo reference points). While these two types of values are often treated interchangeably by academic audiences, they recruit meaningfully different psychological responses. Critically, targets take on properties of goals and carry motivational weight. People aim to reach or surpass a target, exerting extra effort to shift from an outcome below the target to one at or above it. In contrast, anchors act as motivationally inert starting points for subsequent judgments. Although people’s judgments are biased in the direction of anchors, they are not especially likely to move their judgment from one side of an anchor to the other. This distinction can lead to meaningful differences in understanding and generalizing results of one process versus the other. We introduce a new and easy to use approach for classifying values as anchors or targets based on satisfaction ratings accompanied by distributional properties of responses. We present a meta-analysis of this technique applied to existing literature, examining values that are presumed to act as either anchors or targets.

Researchers and practitioners in marketing, economics, and public policy often use preference elicitation tasks to forecast real-world behaviors. These tasks typically ask a series of similarly structured questions. The authors posit that every time a respondent answers an additional elicitation question, two things happen: (1) they provide information about some parameter(s) of interest, such as their time preference or the partworth for a product attribute, and (2) the respondent increasingly “adapts” to the task—that is, using task-specific decision processes specialized for this task that may or may not apply to other tasks. Importantly, adaptation comes at the cost of potential mismatch between the task-specific decision process and real-world processes that generate the target behaviors, such that asking more questions can reduce external validity. The authors used mouse and eye tracking to trace decision processes in time preference measurement and conjoint choice tasks. Respondents increasingly relied on task-specific decision processes as more questions were asked, leading to reduced external validity for both related tasks and real-world behaviors. Importantly, the external validity of measured preferences peaked after as few as seven questions in both types of tasks. When measuring preferences, less can be more.

Why do consumers embrace some algorithms and find others objectionable? The moral relevance of the domain in which an algorithm operates plays a role. The authors find that consumers believe that algorithms are more likely to use maximization (i.e. attempting to maximize some measured outcome) as a decision-making strategy than human decision makers (Study 1). Consumers find this consequentialist decision strategy to be objectionable in morally relevant tradeoffs and disapprove of algorithms making morally relevant tradeoffs as a result (Studies 2, 3a, & 3b). Consumers also object to human employees making morally relevant tradeoffs when they are trained to make decisions by maximizing outcomes, consistent with the notion that their objections to algorithmic decision makers stem from concerns about maximization (Study 4). The results provide insight into why consumers object to some consumer relevant algorithms while adopting others.

This chapter summarizes experimental work exploring how individual beliefs about the personally disruptive character of transformative experiences are influenced by intuitive theories of what a self fundamentally is, at the current moment and over time. Judgments of disrupted personal identity are influenced by views of the causal centrality of a transformed trait to a person’s self-concept, with changes in more central features perceived as more disruptive to self-continuity. Furthermore, the type of change matters: unexpected or undesirable changes to personal features are viewed as more disruptive to self-continuity than changes that are consistent with a person’s expected developmental trajectory. The degree to which an individual considers a particular personal change to be disruptive will affect how he or she makes decisions about, reacts to, and copes with this experience.

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from 2 separate large samples (total N > 15,000) were then randomly assigned to complete 1 version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: Materials from different teams rendered statistically significant effects in opposite directions for 4 of 5 hypotheses, with the narrowest range in estimates being d = -0.37 to + 0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for 2 hypotheses and a lack of support for 3 hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, whereas considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

This chapter rehearses the argument made throughout the book: the natural world, though full of suffering and violence, is not fallen. Instead, the evolutionary process is the result of God, in love, allowing the creation to “selve” even in ways that bring harm. God does not leave the creation in this state, but accompanies and works with creatures and events to redeem suffering in both this-worldly and other-worldly ways.

People often make tradeoffs between current and future benefits. Some research frameworks suggest that people treat the future self as if it were another person, subordinating future needs to current ones just as they might subordinate others' needs to their own. Although people make similar choices for future selves and others in some contexts, it remains unclear whether these behaviors are governed by the same decision policies. So, we identify and compare the unique influence of four relevant factors (need, deservingness, liking, and similarity) on monetary decisions in both the interpersonal and intrapersonal domains. Do people treat the future self and others similarly? Yes and no. Yes, because the influence of these factors on allocations is similar for both types of targets. No, because monetary allocations to the future self are consistently higher than allocations to others. Although the future self is treated like others in some ways, important differences remain that are not fully captured by this analogy.

How do people think about whether the person they will be in the future is substantially the same person they will be today, or substantially different, and how does this affect consumer decisions and behavior? This chapter discusses several perspectives about which changes over time matter for these judgments and downstream behaviors, including the identity verification principle: people's willful change in the direction of an identity that they hope to fulfill. The authors' read of the literature on the self-concept suggests that what defines a person (to themselves) is multifaceted and in almost constant flux, but that understanding how personal changes relate to one's own perceptions of personal continuity, including understanding the distinction between changes that are consistent or inconsistent with people's expectations for their own development, can help us to understand people's subjective sense of self and the decisions and behaviors that follow from it.

Many decisions require making tradeoffs between the present and the future. Although a variety of perspectives have been applied to study these intertemporal trade-offs, in this chapter we will focus on research that examines how thoughts about one’s future self affect decisions with delayed consequences. To do so, we will discuss three theoretical perspectives on the future self: the future self as another, continuity between selves, and failures of imagination. Throughout, we examine the myriad considerations that influence decisions made on behalf of the future self in many domains (including finance, health, ethical decision-making, and child development) as well as interventions that have been found to change the way that people think about the future self and potentially promote more prudent behavior. We close by proposing several questions for future research.

The study of how people make judgments and decisions began in cognitive science (the primary JDM conference literally was founded as a workshop at the Psychonomics conference). However, over time the area of judgment and decision-making (JDM) has moved apart from its cognitive roots, despite the high overlap in underlying research questions. However, greater interaction between cognitive and JDM research could yield benefits to both from cross-pollination (Bartels and Johnson 2015), including in terms of methods, types of relevant data and underlying questions. This workshop is designed to foster such interaction. The talks will explore some productive areas of overlap between cognitive research and judgment and decision-making research. Workshop structure. We plan a one-day workshop comprising 12 talks, each approximately 25 minutes. We also plan to have a one-hour panel discussion with all speakers on opportunities for leveraging cognitive and computational approaches to make new advances on long-standing questions in judgment and decision making.

We propose that methods from the study of category-based induction can be used to test the descriptive accuracy of theories of moral judgment. We had participants rate the likelihood that a person would engage in a variety of actions, given information about a previous behavior. From these likelihood ratings, we extracted a hierarchical, taxonomic model of how moral violations relate to each other (Study 1). We then tested the descriptive adequacy of this model against an alternative model inspired by Moral Foundations Theory, using classic tasks from induction research (Studies 2a and 2b), and using a measure of confirmation, which accounts for the baseline frequency of these violations (Study 3). Lastly, we conducted focused tests of combinations of violations where the models make differing predictions (Study 4). This research provides new insight into how people represent moral concepts, connecting classic methods from cognitive science with contemporary themes in moral psychology.

Framing a contract's cost as a series of payments over time structures how people mentally account for the contract's benefits. For example, when people are asked to donate to a charity once a year (aggregate pricing), they imagine the benefits they will feel from a single, large donation. In contrast, if the charity frames its request in terms of the equivalent daily donation (periodic pricing), people consider the benefits from making many smaller donations, which is often a more enticing prospect than a single gift. Eight lab experiments and a field test examine how periodic pricing influences purchase intentions. Periodic prices can increase perceived benefits, particularly when people value the first few units of a product each more than additional units of consumption. More frequent payments can help people appreciate recurring pleasures and increase the likelihood of purchasing.