Journal of Behavioral Decision Making最新文献

This paper is a meta-analysis of experimental studies dealing with the impact of incidental emotions (happiness, sadness, fear, and anger) on financial risk-taking, so as to explain traditional heterogeneity of outcomes in the literature. After devising a standard search strategy and including studies that comply with a list of eligibility criteria, we code 114 effect sizes at the treatment level from 26 selected articles, and a battery of moderator variables representing design and sample characteristics. Meta-regressions with adjusted predictions find causal impact of fear on risk aversion, albeit to a small extent. On the contrary, average null effects characterize happiness, sadness, and anger. It also turns out that when studies provide financial incentives, country-level individualism moderates the relationship between emotions and risk-taking by increasing risk propensity. We discuss possible interpretations of our findings.

More extreme temperature and precipitation events are defining features of climate change, and higher volatility in asset prices is a defining feature of globalization. Four experiments (two preregistered; total N = 2086) found that exposure to a high degree of variability in a given domain shifted people's preferences toward more popular products, that is, products rated by a larger number of consumers. This finding replicated across different experimental manipulations of variability, including graphs depicting either high or low variability in annual rainfall or temperature (Experiments 1 and 2), and in the experienced outcomes of dice rolls, which were manipulated to be perceived as having high or low variability (Experiment 3). The results generalized across different consumer choices, including services (Experiment 1) and products (Experiments 2 and 3). After exposure to higher variability, participants who received a more popular but lower rated option felt less anxious than those who received a less popular but higher rated option, indicating that choosing popular products serves to reduce the anxiety induced by higher variability (Experiment 4). This research highlights both a novel consequence of exposure to greater variability and a novel antecedent of people's preference for popular options.

The public display of election poll results is often manipulated to influence voter predictions about the race. Narrow scaling is one such manipulation that involves truncating the chart's vertical axis such that its range extends closely around the values of the bars. This manipulation exacerbates the visual difference between bars, making the margin appear larger than an unbiased representation would suggest. The current research examines whether narrow scaling of a bar chart depicting the degree of support for political candidate affects voters' predictions about election outcomes. In three experiments, conducted during the 2022 US gubernatorial and senate elections, we displayed published polls to potential voters using a wide- or a narrow-scaled bar chart. We found that when the scale is narrow, voters are more likely to predict that the leading candidate in the poll will win the election and by a larger margin. This scaling bias occurs despite voters' relative skepticism about narrow-scaled polls. We further find that the scaling effect is attenuated when the poll margin is relatively large and enhanced when numerical value labels are removed from the graphic display.

The aim of the present research was to investigate the involvement of mental imagery in people's choices under risk. We tested the general idea that decision makers can use visual mental images (visual mental simulations) to pre-experience how rewarding or threatening future outcomes of risky behavior will be and try out the potential consequences of their risky activities. The paper reports the results of three preregistered studies (including one experiment) showing that the valence of mental imagery is related to the willingness to take risky actions and that people spontaneously use mental imagery as an informative decision input. In Study 1, we found that the more positive mental images people produced when faced with risk, the more willing they were to take risky actions representing different risk domains. Study 2 extended the results of Study 1, indicating that the valence of mental imagery has a causal effect on participants' risk taking willingness. Qualitative analysis based on independent judges' evaluations conducted in Studies 1 and 2 documented that, when requested, participants could easily generate visual mental images illustrating the consequences of their risky choices. Finally, with Study 3, we found that participants declared using mental imagery as a decision input (i.e., a source of information that helps them make choices) even when they were not instructed to do so. However, the frequency of reporting images as decision inputs differed across risky activities.

People exhibit scope insensitivity: Their expressed valuation of a problem is not proportionate with its scope or size. To address scope insensitivity in charitable giving, Hsee et al. (2013) developed the (Classical) Unit Asking technique, where people are first asked how much they are willing to donate to support a single individual, followed by how much they are willing to donate to support a group of individuals. In this paper, we explored the mechanisms, extensions, and limitations of the technique. In particular, we investigated an extension of the technique, which we call Sequential Unit Asking (SUA). SUA asks people a series of willingness-to-donate questions, in which the number of individuals to be helped increases in a stepwise manner until it reaches the total group size. Across four studies investigating donation judgments (total $�N�=�2045$), we did not find evidence that willingness to donate (WTD) judgments to the total group increased with larger groups. Instead, our results suggest that Unit Asking (sequential or classical) increases donation amounts only through a single one-off boost. Further, we find evidence in three out of four studies that the SUA extension increases WTD judgments over Classical Unit Asking. In a fifth study ($�N�=�537$) using a contingent valuation design (instead of donation judgments), we find scope sensitivity using all asking techniques. We conclude that, while it is difficult to create scope sensitivity in WTD judgments, SUA should be considered a promising approach to increase charitable donations.

This research explores the hypothesis that third-party decision makers will be less likely to switch from a suboptimal default payoff to a more efficient alternative one when payoff receipts have been identified than when they have not, even when identification conveys no relevant information. While Studies 1 and 2 establish this identifiability effect by manipulating identifiability with real names (“S. Jones” / “R. Smith”) in realistic decision making vignettes, Studies 3 and 4 replicate the effect by manipulating identifiability with simple designations (“Participant A” / “Participant B”) in incentivized decision paradigms that involve real monetary payoffs. And while Studies 1 and 2 demonstrate the identifiability effect among third-party decision makers choosing to switch from a default payoff to a more efficient alternative payoff, Study 3 instantiates the identifiability effect even when changing the status quo is mandatory. Finally, both Studies 3 and 4 probed for possible psychological mechanisms, finding that analytical processing mode, in particular, may play a role in these third-party allocations.

In two studies, we investigated the effectiveness of an automated form of calibration training via individualized feedback as a means to improve calibration in forecasts. In Experiment 1, this training procedure was tested in a realistic forecasting situation, namely, predicting the outcome of baseball games. Experiment 2 was similar but used a more controlled forecasting task, predicting whether competitors would bust in a modified version of blackjack. In comparison to a control group without training, participants provided with calibration training had reduced confidence levels, which translated into reduced overconfidence and better overall calibration in Experiment 2. The results across both studies suggest that an automated form of individualized performance feedback can reduce the confidence of initially overconfident forecasters.

How should managers supervising multiple teams allocate bonuses—based on each team's size or based on each team's contribution? According to the commonly accepted equity norm for allocating rewards, managers should distribute bonuses based on the relative contributions of the team. In contrast, we propose that managers are instead distracted by the number of employees in each team and neglect team contribution highlighted in the equity norm. Pilot Studies 1 and 2 confirmed that in both individual- and team-based bonus allocation situations, people preferred and actually allocated rewards according to the equity norm rather than the equality norm or the need norm when only contribution was manipulated. However, Study 1, a laboratory experiment, revealed that individuals assigned to the role of a manager allocated more bonuses to the larger team even though the two teams' actual work output (in terms of the number of units of work completed) was nearly identical. Study 2 replicated the key findings of Study 1 using a sample of managers supervising teams in organizations. Study 3 developed an information nudge—highlighting the team contribution—that reduced this bias. Together, these studies indicate a novel team-size bias that creeps in when managers allocate rewards to multiple teams and document an information nudge to reduce this bias.

Group-level risk attitudes are often studied across psychology domains (e.g., binge drinking among college students, and driving risk by gender). In measuring these differences by self-report, such work relies on the assumption that those measures of risk attitude function equivalently across demographic groups—that is, that the measure employed has the property of measurement invariance. Here, we examine the measurement invariance properties of a widely used risk measure, the Domain-Specific Risk-Taking (DOSPERT) scale across different demographic groups. A secondary goal was to determine whether a hierarchical or bifactor model better fits the data. Data were collected from Prolific using a stratified sampling approach to ensure sufficient and unconfounded sampling of sex, socioeconomic status (SES), and race (N = 412). Sample groups consisted of approximately 50 participants each, based on the intersection of three dichotomized demographic groups (high vs. low SES, White vs. non-White, and female vs. male). Subjects completed the 30-item form of the DOSPERT assessing likelihood, perceived benefit, and riskiness of the same 30 behaviors. The bifactor models showed a superior fit to the hierarchical models and were used in subsequent analyses. These analyses demonstrated that no models fit generally acceptable criteria for configural fit, and many models additionally fail cutoffs for metric and scalar invariance. This study adds to findings that the DOSPERT does not perform equivalently across demographic groups. We suggest development of a scale of risk that is invariant across commonly assessed demographic factors.

Many collective action problems are inherently linked to honesty. By deciding to behave honestly, people contribute to solving the collective action problem. We use a laboratory experiment from two sites (n = 331 and n = 319) to test whether honest preferences can drive cooperation and whether these preferences can be differentially activated by framing. Subjects participate in an asymmetric information variant of the public goods game in one of two treatments that vary only in their wording: The Contribution Frame uses a standard public good game framing, while in the Honesty Frame, words aimed to trigger honesty are used. We measure subjects' honesty in three ways using the (i) sender–receiver task, (ii) the die-roll task, and (iii) self-reported honesty levels and account for other-regarding preferences and social norms to disentangle key alternative motives. We find that all three measures of honesty preferences robustly predict contributions, as do other-regarding preferences and empirical expectations but not normative expectations. Additionally, honesty preferences predict contributions in the Honesty Frame but not in the Contribution Frame, although the difference between these is not consistently significant. Finally, we find no differences in average cooperation across the treatments.