Clarifying the ideal point: Can it reduce regret?

Abstract

Although a considerable number of options increases the likelihood of encountering an ideal choice, it also imposes excessive cognitive load, making it difficult to compare options thoroughly and thereby leading to stronger regret and lower satisfaction. This phenomenon, known as the choice overload effect, disappears when cognitive demands are alleviated, such as by making an ideal point available. However, previous studies have investigated the moderating role of ideal point availability only at the cognitive and behavioral levels, leaving it unclear whether making an ideal point available reduces regret when choosing from too many options. This study investigated whether making an ideal point available could reduce the regret experienced when selecting from many options in a chocolate selection task. An online experiment employing a hypothetical scenario and a laboratory experiment involving chocolate tasting were conducted. Ideal point availability (available vs. unavailable) and the number of chocolates presented were manipulated (4 vs. 16 options). The results indicated that under the 16-option condition, participants experienced less regret when the ideal point was available than when it was not. In the laboratory experiment, regret was lower when the choice set was small and the ideal point was available. These findings suggest that making the ideal point available may enable choices that minimize regret.

Regret is a negative emotion that arises when one imagines a better outcome could have occurred by making a different decision; it is typically characterized by self-blame for unfavorable consequences (Connolly & Zeelenberg, 2002; Zeelenberg & Pieters, 2007).

One of the key factors influencing experienced regret is the number of options available. Although more options increase the chance of finding an ideal one, previous studies have reported the “choice overload effect,” which reflects the negative consequences of having many options in the decision-making process (e.g., Iyengar & Lepper, 2000). Having too many options increases the cognitive load, making it difficult to adequately compare options, which leads to stronger regret (e.g., Inbar et al., 2011; Sagi & Friedland, 2007) or lower satisfaction with the decision (Iyengar & Lepper, 2000).

Chernev (2003a, 2003b) demonstrated that making an “ideal point” available—that is, clarifying one’s attribute preferences (e.g., deciding to look for a chocolate with high cacao content and almonds, rather than just a “tasty” one) —lowers cognitive load and moderates the choice overload effect. As reviewed by Chernev et al. (2015), the choice overload effect has been discussed using various indicators, including switching likelihood, decision confidence, and emotional responses (e.g., satisfaction and regret). Among these, regret is of particular importance. Regret is not merely a negative emotional consequence of a decision; it also has a learning function that can influence future decision (e.g., Zeelenberg & Pieters, 2007). Therefore, examining how ideal point availability moderates regret is crucial for understanding how people can improve future decisions. However, it remains unclear whether this moderation occurs in choice overload situations.

Addressing this gap, the present study investigated whether making an ideal point available through clarifying preferences before decision can mitigate regret after choosing from too many options. Following previous studies on the choice overload effect (e.g., Iyengar & Lepper, 2000; Chernev, 2003a, 2003b), we used a chocolate selection task. In previous studies on regret (e.g., Sagi & Friedland, 2007), regret has been typically induced by providing participants with negative feedback about the outcomes of their decisions. Accordingly, Experiment 1 used a hypothetical scenario in which participants imagined an unfavorable outcome. To address the limitations of this method, Experiment 2 was conducted in a laboratory setting, where participants actually tasted the chocolate they had selected.

Aim and Hypothesis

This study conceptually replicates and extends the findings of Chernev (2003b) to the emotional domain of regret. Chernev (2003b) demonstrated that the effect of ideal point availability on cognitive and behavioral outcomes differs between large and small option sets. The primary aim of the present study is to investigate whether this interaction effect also applies to post-decision regret. When choosing from a large set of options (e.g., 16), the cognitive load required to compare all alternatives is high. In this situation, having a clearly defined ideal point can significantly reduce this cognitive load by providing a clear benchmark for evaluation, thereby mitigating negative outcomes. Conversely, when choosing from a small set of options (e.g., 4), the cognitive load is inherently low. Therefore, the clarifying effect of an ideal point is expected to be minimal or absent.

Based on this reasoning, we formulated the following hypothesis: An interaction between the number of options and ideal point availability would be observed. Specifically, we predicted that participants with an available ideal point would experience less regret than those without one in the 16-option condition, whereas this effect would be diminished or absent in the 4-option condition.

Ethical Considerations

This study was approved by the Ethics Review Committee of the University of Tokyo (approval number: UTSP-23020). All participants provided written informed consent after being fully informed of the study’s purpose and procedures. Participation was voluntary, and individuals could withdraw at any time without penalty. Collected data were anonymized and stored securely in accordance with institutional guidelines.

Experiment 1

In most studies on regret, regret is typically induced by providing participants with negative feedback about their decision outcomes (e.g., Sagi & Friedland, 2007). Accordingly, we first employed a hypothetical scenario method in which participants imagined an unfavorable outcome after a decision.

Participants

An online experiment was conducted with 37 Japanese university students (14 men and 23 women; M_age=19.00, SD=.87). Participants were randomly assigned to one of four conditions: the 4-option/unavailable condition (n=9), the 4-option/available condition (n=13), the 16-option/unavailable condition (n=7), or the 16-option/available condition (n=8).

Experimental Design

The independent variables were ideal point availability (available vs. unavailable) and number of options (4 vs. 16), and the dependent variable was regret for each decision. The study employed a 2 (ideal point availability: available vs. unavailable)×2 (number of options: 4 vs. 16) between-subjects factorial design.

Procedure

The participants participated in an online chocolate selection experiment using a hypothetical scenario conducted via the Internet on their personal computers. At the beginning of the experiment, the participants answered two questions on a four-point scale about the frequency with which they usually eat chocolate and their preferences for chocolate². Subsequently, they read a scenario describing the following: “You are participating in an experiment at your university where you will taste chocolates, and you want to choose a chocolate that matches your preferences.” They were asked to imagine this situation as vividly as possible before proceeding to the chocolate selection task, which consisted of three phases: (a) preference clarification, (b) selection, and (c) emotion evaluation tasks.

Preference clarification task

As ideal point availability manipulation, participants were randomly assigned to either the available condition, in which they performed a task to clarify their preferences for chocolate, or the unavailable condition, in which they did not (they were only presented with the list of the chocolate attributes). The task used in the available condition involved clarifying preferences within the options’ attributes and prioritizing them (Chernev, 2003a, 2003b). Specifically, the participants evaluated the attractiveness of four items within each of the four chocolate attributes, rating them on a scale of 0 to 100, such that the total score for each attribute was 100. The four attributes were chocolate type (solid, truffle, praline, and caramel), chocolate mix (dark, milk, white, and ruby), flavor (original, vanilla, strawberry, and berry), and nut content (without nuts, almonds, hazelnuts, and macadamia nuts). They ranked the four attributes in order of importance.

Selection task

Participants were presented with a list of information about multiple chocolates and asked to select the chocolate they most wanted to eat. The chocolates were from the GODIVA brand, following the precedent set by Chernev (2003b). To enhance ecological validity and provide realistic descriptions, the detailed information for each chocolate (e.g., chocolate type, flavor, and nut content) was presented using the official product descriptions from the GODIVA website³. Participants were randomly assigned to either the four-option condition or the 16-option condition, in which four or 16 chocolates were presented, respectively.

Emotion evaluation task

After completing the chocolate selection, participants were presented with a continuation of the scenario: “Upon tasting the chocolate you selected, you find it differs from what you imagined and is not to your liking.” Imagining the scenario, participants responded to items assessing their level of satisfaction and regret with the decision using a seven-point scale (0=not at all; 6=very much). Additionally, a seven-point scale (0=too few options; 6=too many options) served as a manipulation check for the perceived number of options (Iyengar & Lepper, 2000). This item was used as a manipulation check to confirm that the 16-option condition was perceived as involving greater choice overload than the four-option condition. Finally, the participants provided their demographic information, including age and sex, to complete the experiment.

Results

Perception of choice overload (manipulation check)

Participants in the 16-option condition (M=3.71, SD=1.23) perceived the options as significantly more excessive than those in the four-option condition (M=2.50, SD=1.21; t(32.70)=−3.00, p<.001, d=−.99). Furthermore, the mean score for the 16-option condition was above the scale’s midpoint of 3 (on a scale from 0 to 6), indicating that the number of options was perceived as too many.

Hypothesis testing

Given the exploratory nature of this experiment and the small sample size, our results will be based not only on statistical significance (p<.05) but also on the magnitude of the effect sizes. The means and standard errors of regret and satisfaction scores for each condition are presented in Figure 1. A two-way analysis of variance (ANOVA) with regret as the dependent variable was conducted. The main effect of ideal point availability was not statistically significant but also showed a medium effect size (F(1, 33)=4.02, p=.05, η²=.11), indicating a tendency for participants in the available condition (M=3.77, SD=1.69) to experience less regret than those in the unavailable condition (M=2.67, SD=1.72). There was no significant main effect of the number of options (F(1, 33)=.03, p=.87, η²=.001). The interaction effect between the number of options and ideal point availability was not statistically significant but the effect size was medium (F(1, 33)=3.77, p=.06, η²=.10). Given our specific a priori hypothesis and the large effect size of the interaction, we conducted a simple main-effects analysis. As predicted, in the 16-option condition, participants experienced significantly less regret when the ideal point was available (M=2.00, SD=.93) than when it was not (M=4.08, SD=1.71) (t(33)=2.79, p=.009, d=.97). In contrast, in the 4-option condition, there was no significant difference in regret between the available and unavailable conditions (t(33)=−.11, p=.91, d=−.04).

Figure 1 Experiment 1: Mean and Standard Error of Regret and Satisfaction across conditions

By contrast, a two-way ANOVA with satisfaction as the dependent variable found neither the main effect of the number of options (F(1, 33)=.53, p=.47, η²=.02), nor main effect of ideal point availability (F(1, 33)=.002, p=.97, η²=.0001), nor the interaction effect (F(1, 33)=2.19, p=.15, η²=.06) were significant. While the mean scores for regret exceeded 3 in all conditions except the ideal-available/16-option condition, satisfaction across all conditions was <3 (on a seven-point scale ranging from 0 to 6).

Discussion

The results of the statistical tests did not support our hypothesis, but the magnitude of the effect size suggested that the fundamental idea behind the hypothesis is valid. While the interaction between the number of options and ideal point availability was not statistically significant, the pattern of the means was consistent with our prediction and accompanied by a large effect size. As hypothesized, when faced with 16 options, participants in the available condition experienced significantly less regret than those in the unavailable condition. This pattern provides tentative evidence that ideal point availability may moderate the effect of the number of options on post-decision regret. However, as this was an online experiment using a hypothetical scenario in which participants were instructed to imagine a negative outcome, it remains unclear whether this tendency can be observed in actual decision-making contexts. Therefore, in Experiment 2, the participants were asked to taste the chocolate they selected in a laboratory.

Experiment 2

Participants

A laboratory experiment was conducted with 25 Japanese university students (10 men and 15 women; M_age=20.88, SD=1.17). Participants were randomly assigned to one of four conditions: the 4-option/unavailable condition (n=6), the 4-option/available condition (n=7), the 16-option/unavailable condition (n=7), or the 16-option/available condition (n=5).

Experimental Design

The independent variables were ideal point availability (available vs. unavailable) and number of options (4 vs. 16), and the dependent variable was regret for each decision. The study employed a 2 (ideal point availability: available vs. unavailable)×2 (number of options: 4 vs. 16) between-subjects factorial design.

Procedure

The participants were recruited individually into the laboratory and signed an informed consent form before participating in the experiment. Participants then engaged in a chocolate selection task consisting of three phases: (a) preference clarification, (b) selection, and (c) emotion evaluation tasks. This procedure largely replicated the hypothetical chocolate selection process in Experiment 1. Participants in Experiment 1 rated their degree of regret by imagining a situation in which they chose chocolate that did not taste as well as expected, whereas participants in Experiment 2 rated regret by actually tasting the chocolate. Two items were used to assess regret, following Iyengar and Lepper (2000): “Do you regret choosing and eating that chocolate?” and “Do you think there was a better chocolate among the list of chocolates?” The average of the two items was used as the regret score⁴. Subsequently, participants were asked to engage in another selection task, which was beyond the focus of this study and is thus not discussed in detail. After completing the task, the participants were debriefed about the study’s purpose, and their consent for data usage was reaffirmed before concluding the experiment.

Results

Perception of choice overload (manipulation check)

As in Experiment 1, participants in the 16-option condition (M=4.08, SD=.52) perceived a significantly stronger sense of choice overload compared to participants in the four-option condition (M=2.31, SD=.95; t(18.81)=−5.88, p<.001, d=−2.30). The mean score for the 16-option condition was also well above the scale’s midpoint of 3, confirming that the number of options was perceived as too many.

Hypothesis testing

The means and standard errors of regret and satisfaction scores for each condition are presented in Figure 2.

Figure 2 Experiment 2: Mean and Standard Error of Regret Score and Satisfaction across conditions

A two-way ANOVA with regret score as the dependent variable was conducted⁵. There were two significant main effects. The main effect of the number of options was significant (F(1, 21)=9.30, p=.006, η²=.31), indicating that participants experienced less regret in the 4-option condition (M=.73, SD=.56) than in the 16-option condition (M=1.42, SD=.73). The main effect of ideal point availability was also significant (F(1, 21)=9.09, p=.006, η²=.30), indicating that participants experienced less regret when the ideal point was available (M=.67, SD=.49) than when it was not (M=1.42, SD=.73). Contrary to our hypothesis, the interaction effect was not significant (F(1, 21)=.72, p=.40, η²=.03).

By contrast, a two-way ANOVA with satisfaction as the dependent variable found that neither of the main effect of the number of options (F(1, 21)=.20, p=.66, η²=.01), nor main effect of ideal point availability (F(1, 21)=.46, p=.51, η²=.02), nor the interaction effect (F(1, 21)=.19, p=.67, η²=.01) were significant. While the mean scores for regret were <3 (on a seven-point scale ranging from 0 to 6), the mean scores for satisfaction exceeded five across all conditions.

Discussion

Unlike Experiment 1, Experiment 2 yielded significant main effects of both the number of options and ideal point availability on regret, but no significant interaction. Specifically, participants experienced less regret when the number of options was small (4 vs. 16) and when their ideal point was made available. A key difference between the two experiments lies in the nature of the decision consequences. Experiment 1 involved a hypothetical decision based on a scenario, whereas in Experiment 2, participants tasted the chocolate they selected. This likely increased participants’ involvement in the decision-making process, prompting more careful deliberation. As Chernev et al. (2015) noted, decisions involving actual consumption require greater cognitive effort than hypothetical ones. Therefore, it is plausible that in Experiment 2, even the 4-option condition imposed a sufficient cognitive load for the effect of ideal point availability to emerge.

When an ideal point is available, the criteria for ideal choice become more defined, thereby limiting the factors for comparison among options. Consequently, the regret experienced by comparing one’s chosen option with unchosen options is reduced. However, it should be noted that the overall levels of experienced regret were quite low, suggesting a potential floor effect. In line with previous studies, GODIVA chocolates were used as the experimental stimulus in this study, which led many participants to report that they were very satisfied with the chocolates they selected and tasted.

General Discussion

This study provides evidence that clarifying an ideal point can mitigate the regret associated with choice overload, extending previous findings from cognitive and behavioral domains (Chernev, 2003a, 2003b) to an emotional one. This has practical implications for consumers. In a marketplace where increased options can lead to regret (Chernev et al., 2015), our findings suggest that people can take advantage of more options by clarifying their ideal points before making a choice. Furthermore, considering the learning function of regret (Zeelenberg & Pieters, 2007), future research should investigate how and to what extent the regret reduction shown in this study helps individuals navigate rich options and make better decision in subsequent choice opportunities.

Several limitations of this study should be noted. First, the sample size was small. This study should be viewed as an exploratory first step, primarily intended to test whether the procedure of actual tasting could adequately elicit regret in this context. Future research is needed to replicate these results with a larger sample, for which an a priori power analysis based on the effect sizes reported here would be essential. Second, the regret experienced in Experiment 2, in which participants tasted the selected chocolate, was notably lower. In Experiment 1, the mean regret exceeded three in all conditions, except for the available condition with 16 options. In contrast, in Experiment 2, the mean regret scores were <3 across all conditions. In both experiments, GODIVA chocolates were used as the experimental stimulus. However, in Experiment 1, all the participants were instructed to imagine a situation in which the selected chocolate was not liked as much as expected when rating their regret. In Experiment 2, where participants tasted the chocolate, such a scenario did not materialize, potentially leading many participants to experience less regret. Supporting this interpretation, in Experiment 1, satisfaction ratings were <3 across all conditions, whereas in Experiment 2, satisfaction ratings were >5 in all conditions. Given that regret arises in response to unfavorable outcomes, it may not be adequately elicited when all available chocolates are uniformly enjoyable.

Footnotes

¹ We would like to express our gratitude to Dr. Shuma Iwatani for his support in collecting data for Experiment 1, and to Mr. Kado, Ms. Sugiura, and Ms. Suzuki for their assistance in conducting Experiment 2.

² Referring to Iyengar and Lepper (2000), we confirmed that there were no between-condition differences in frequency of chocolate consumption and intensity of preference for chocolate in both Experiments before testing the hypothesis (see Supplementary Materials).

³ For example, see the official GODIVA Japan website: https://www.godiva.co.jp/items/. All product information was retrieved from this site. Last accessed October 16, 2025.

⁴ Although the two items were not significantly correlated (Spearman’s ρ=.27, p=.194), we created a composite score following Iyengar and Lepper (2000). This approach is theoretically grounded, as regret has both emotional and cognitive-counterfactual components. See Supplementary Materials for separate analyses of each item.

⁵ The analysis for the regret item only showed the main effect of ideal point availability was not statistically significant but also showed a large effect size (F(1, 21)=3.65, p=.07, η²=.15), and the interaction effect between the number of options and ideal point availability was not statistically significant but the effect size was large (F(1, 21)=3.86, p=.06, η²=.16), supporting the underlying hypothesis. Conversely, the results for the counterfactual item analysis were consistent with the main findings of this hypothesis testing (See Supplementary Materials for details).

Disclosure Statement

The authors declare no conflicts of interest. This study was funded by the Management Expense Grant (the University of Tokyo).

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