Choice Difficulty Research Articles

When the going gets tough: Power affects the process of making tough decisions

ABSTRACT Powerful roles often require individuals to cope with impactful, complicated decisions. The present article reports two experiments investigating the effect of manipulated power mindset on the process of decision-making under different conditions: high vs. low choice conflict (Exp. 1) or high vs. no cognitive load (Exp. 2). Results showed that under the high-choice conflict and high-cognitive load conditions, high-power participants were more likely than low-power participants to take less time, adopt an alternative-based (rather than attribute-based) strategy, rate the tasks as easier, and report higher confidence in and satisfaction with their decisions. Power had no effect on the decision-making process under the low-choice conflict and no-cognitive load conditions. These results suggest that power interacts with choice difficulty to affect the decision-making process.

Marketing the use of headgear in high contact sports

High contact sports have gained popularity among consumers, who often seek thrills and the feeling of invincibility by risking their well-being. One major health risk associated with these sports is head injuries, including trauma, concussion, and sleep disruption. In this research, we investigate the effect of consumers’ product choice difficulty on their health risk assessments. We illustrate a novel mediating route by documenting how and when choice maximization can help consumers make the optimal choice when faced with the many products available in the market. To aid their decisions, consumers require communication about the health benefits of the product (first-stage boundary condition) but not at the expense of reducing their game-playing enjoyment (second-stage boundary condition). The paper concludes with contributions to and implications for theory and practice and a research agenda to guide future inquiries in this under-researched area.

Associations Between Delay Discounting and Connectivity of the Valuation-control System in Healthy Young Adults

The process of valuation assists in determining if an object or course of action is rewarding. Delay discounting is the observed decay of a rewards’ subjective value over time. Encoding the subjective value of rewards across a spectrum has been attributed to brain regions belonging to the valuation and executive control systems. The valuation system (VS) encodes reward value over short and long delays, influencing reinforcement learning and reward representation. The executive control system (ECS) becomes more active as choice difficulty increases, integrating contextual and mnemonic information with salience signals in the modulation of decision-making. Here, we aimed to identify resting-state functional connectivity-based patterns of the VS and ECS correlated with value-setting and delay discounting (outside-scanner paradigm) in a large (n = 992) cohort of healthy young adults from the Human Connectome Project (HCP). Results suggest the VS may be involved in value-setting of small, immediate rewards while the ECS may be involved in value-setting and delay discounting for large and small rewards over a range of delays. We observed magnitude sensitive connections involving the posterior cingulate cortex, time-sensitive connections with the ventromedial and lateral prefrontal cortex while connections involving the posterior parietal cortex appeared both magnitude- and time-sensitive. The ventromedial prefrontal cortex and posterior parietal cortex could act as “comparator” regions, weighing the value of small rewards against large rewards across various delay duration to aid in decision-making.

The behavioral analysis of choice difficulty states during clothing online shopping

PurposeChoice overload in e-commerce induces choice difficulty, which is detrimental to shopping decision-making. The purpose of this paper is to provide relatively simple and effective methods and indicators to detect and assess the choice difficulty states of customers during clothing online shopping.Design/methodology/approachIn order to find out the behavioral performance of choice difficulty states during clothing online shopping, the authors performed the following steps: at first, the authors conducted an experiment to record the videos of the purchasing process during clothing online shopping. Then, the authors carried out the behavioral analysis of customers, correlating each behavioral index to choice difficulty states.FindingsThe results of the behavioral analysis in this study have indicated that three types of behavior were significantly correlated to the choice difficulty states of customers.Practical implicationsIt is expected that it would be possible to use the threshold values of behavioral indicators to determine whether and when the customer is suffering from choice phobia disorder. Based on the findings, a recommender system with timely interventions to help customers with choice difficulty to make shopping decisions will be developed in the future.Originality/valueThis is the first reported study that explores the possibility of using behavioral indicators to detect choice difficulty, which will remain helpful to the scientific community to start further customer-centered research work and development of clothing online shopping.

Artificial intelligence and the new forms of interaction: Who has the control when interacting with a chatbot?

Advances in artificial intelligence provide new tools of digital assistance that retailers can use to support consumers while shopping. The aim of this research is to examine how consumers react as a function of assistants’ appearance (human- vs. not human-like) and activation (automatic vs. human-initiated). We advance a model of sequential mediation whose empirical validation on 400 participants in two studies shows that non-anthropomorphic digital assistants lead to higher psychological reactance. In turn, reactance affects perceived choice difficulty, which positively reflects on choice certainty, perceived performance and—ultimately—satisfaction. Thus, although reactance might appear as a negative outcome, it eventually leads to higher satisfaction. Furthermore, initiation (system vs. user initiation) does not activate the chain of effects, but significantly interacts with anthropomorphism so that individuals exhibit lower reactance when confronted with human-like digital assistants activated by the consumer. Overall, reactance is highest for non-human like digital assistants that are computer-initiated.

An Empirical Test of the Role of Value Certainty in Decision Making.

Most contemporary models of value-based decisions are built on value estimates that are typically self-reported by the decision maker. Such models have been successful in accounting for choice accuracy and response time, and more recently choice confidence. The fundamental driver of such models is choice difficulty, which is almost always defined as the absolute value difference between the subjective value ratings of the options in a choice set. Yet a decision maker is not necessarily able to provide a value estimate with the same degree of certainty for each option that he encounters. We propose that choice difficulty is determined not only by absolute value distance of choice options, but also by their value certainty. In this study, we first demonstrate the reliability of the concept of an option-specific value certainty using three different experimental measures. We then demonstrate the influence that value certainty has on choice, including accuracy (consistency), choice confidence, response time, and choice-induced preference change (i.e., the degree to which value estimates change from pre- to post-choice evaluation). We conclude with a suggestion of how popular contemporary models of choice (e.g., race model, drift-diffusion model) could be improved by including option-specific value certainty as one of their inputs.

Dorsal Premotor Cortex Neurons Signal the Level of Choice Difficulty during Logical Decisions

Studies on the neuronal correlates of decision making have demonstrated that the continuous flow of sensorial information is integrated by sensorimotor brain areas in order to select one among simultaneously represented targets and potential actions. In contrast, little is known about how these areas integrate memory information to lead to similar decisions. Using serial order learning, we explore how fragments of information, learned and stored independently (e.g., A > B and B > C), are linked in an abstract representation according to their reciprocal relations (such as A > B > C) and how this representation can be accessed and manipulated to make decisions. We show that manipulating information after learning occurs with increased difficulty as logical relationships get closer in the mental map and that the activity of neurons in the dorsal premotor cortex (PMd) encodes the difficulty level during target selection for motor decision making at the single-neuron and population levels.

Surprise, value and control in anterior cingulate cortex during speeded decision-making.

Activity in the dorsal anterior cingulate cortex (dACC) is observed across a variety of contexts, and its function remains intensely debated in the field of cognitive neuroscience. While traditional views emphasize its role in inhibitory control (suppressing prepotent, incorrect actions), recent proposals suggest a more active role in motivated control (invigorating actions to obtain rewards). Lagging behind empirical findings, formal models of dACC function primarily focus on inhibitory control, highlighting surprise, choice difficulty and value of control as key computations. Although successful in explaining dACC involvement in inhibitory control, it remains unclear whether these mechanisms generalize to motivated control. In this study, we derive predictions from three prominent accounts of dACC and test these with functional magnetic resonance imaging during value-based decision-making under time pressure. We find that the single mechanism of surprise best accounts for activity in dACC during a task requiring response invigoration, suggesting surprise signalling as a shared driver of inhibitory and motivated control.

Relieving the regret for maximizers

PurposePrior research consistently found maximizers to experience greater regret over their choice than satisficers. Moreover, research also found maximizers to be trapped in a “maximization-regret-maximization” cycle. This paper aims to assess the role of construal level theory in alleviating regret felt by maximizers.Design/methodology/approachThe authors examine the construal level theory (CLT) in conjunction with the choice context (comparable and non-comparable choices). Three experimental studies tested our assertion that a match between CLT mindset and choice set relieves regret for maximizers.FindingsThe authors show maximizers experience similar levels of regret compared to satisficers when considering comparable options in a concrete mindset, and non-comparable options in an abstract mindset. However, maximizers experience heightened regret in comparison to satisficers when considering non-comparable (comparable) options in a concrete (abstract) mindset. Choice difficulty mediates our effect.Research limitations/implicationsFuture research is needed to replicate our results in real-life settings.Practical implicationsIf marketers think that their product is likely to be compared with other comparable products, they should adopt product-specific information that focusses on how the product would be used. However, if marketers think that consumers will compare across non-comparable products, then they should focus on why their product is the most suitable to fulfil consumers’ needs.Originality/valueThis research represents the first attempt at reducing regret for maximizers and answers the call for an examination of the relationship between maximization and CLT. The research adds to the maximization literature by evidencing a CLT-based strategy that attenuates the negative experience of regret for maximizers.

Learning optimal decisions with confidence

Diffusion decision models (DDMs) are immensely successful models for decision making under uncertainty and time pressure. In the context of perceptual decision making, these models typically start with two input units, organized in a neuron-antineuron pair. In contrast, in the brain, sensory inputs are encoded through the activity of large neuronal populations. Moreover, while DDMs are wired by hand, the nervous system must learn the weights of the network through trial and error. There is currently no normative theory of learning in DDMs and therefore no theory of how decision makers could learn to make optimal decisions in this context. Here, we derive such a rule for learning a near-optimal linear combination of DDM inputs based on trial-by-trial feedback. The rule is Bayesian in the sense that it learns not only the mean of the weights but also the uncertainty around this mean in the form of a covariance matrix. In this rule, the rate of learning is proportional (respectively, inversely proportional) to confidence for incorrect (respectively, correct) decisions. Furthermore, we show that, in volatile environments, the rule predicts a bias toward repeating the same choice after correct decisions, with a bias strength that is modulated by the previous choice's difficulty. Finally, we extend our learning rule to cases for which one of the choices is more likely a priori, which provides insights into how such biases modulate the mechanisms leading to optimal decisions in diffusion models.

Not-so Easy Listening: Roots and Repercussions of Auditory Choice Difficulty in Voice Commerce

In the context of voice shopping, fifteen experiments demonstrate that information presented by voice can be more difficult to process than the same information presented in writing. Consequently, auditory consumers who shop by voice are less able to differentiate between choice options, leading them to choose recommended items more often, but also defer choice at higher rates compared to when the options are presented visually. This auditory choice difficulty stems from greater difficulty comparing auditory options and is related to an increased burden on working memory. Because the difficulty is related to making comparisons, a joint-evaluation—where an option is considered in the context of others—is more likely to be impacted by voice presentation than a separate-evaluation, and joint versus separate preference reversals are less likely by voice. However, voice presentation can negatively affect the evaluation of even a single item when a consumer compares it against a remembered item, a common scenario in the actual marketplace for tasks such as re-orders. Describing choice options in a way that reduces the burden on memory for auditory consumers can reduce processing difficulty and its downstream consequences.

Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services

Music streaming services increasingly incorporate different ways for users to browse for music. Next to the commonly used “genre” taxonomy, nowadays additional taxonomies, such as mood and activities, are often used. As additional taxonomies have shown to be able to distract the user in their search, we looked at how to predict taxonomy preferences in order to counteract this. Additionally, we looked at how the number of categories presented within a taxonomy influences the user experience. We conducted an online user study where participants interacted with an application called “Tune-A-Find”. We measured taxonomy choice (i.e., mood, activity, or genre), individual differences (e.g., personality traits and music expertise factors), and different user experience factors (i.e., choice difficulty and satisfaction, perceived system usefulness and quality) when presenting either 6- or 24-categories within the picked taxonomy. Among 297 participants, we found that personality traits are related to music taxonomy preferences. Furthermore, our findings show that the number of categories within a taxonomy influences the user experience in different ways and is moderated by music expertise. Our findings can support personalized user interfaces in music streaming services. By knowing the user’s personality and expertise, the user interface can adapt to the user’s preferred way of music browsing and thereby mitigate the problems that music listeners are facing while finding their way through the abundance of music choices online nowadays.

Strength of Preference and Decision Making Under Risk

Influential economic approaches random utility models or quantal-response equilibria assume a monotonic relation between error rates and choice difficulty or of in line with widespread evidence from discrimination tasks in psychology and neuroscience. However, while the latter define difficulty through objective dimensions (weight, length, etc), for economic decisions under risk the appropriate dimension remains unclear, with candidates including payoff-irrelevant numerical magnitudes. The very existence of the effects remains largely untested, because fitting models which assume such relations to data simply produces spurious findings. We provide a systematic empirical validation relying on two parsimonious experimental designs. Strength-of-preference effects are explained by expected values objectively-correct answers exist, and by cardinal differences in independently-estimated utilities for preferential choices. Numerical magnitudes produce additional but minor effects. Finally, response times are inversely related to strength of preference, confirming that the observed relations are not as if explanations.

Neural correlates of effort-based behavioral inconsistency

According to the theory of value-based decision making, subjects tend to choose the most valuable among a set of options. However, agents may not be consistent when facing the same decision several times. In this paper, Shannon's entropy (H) is employed as a measure of behavioral inconsistency: it is a central measure of information theory that, applied to decision making, allows the estimation of behavioral preferences among a set of options. We scanned (functional magnetic resonance imaging, fMRI) 24 young (18–25 year) subjects (14 female) while performing a decision-making task, where monetary rewards were devalued by physical effort (minutes running in the treadmill) and risk. Twenty different pairs of options were presented nine times each, and H was calculated for each pair and subject. Behavioral analyses showed that subjective value (SV) significantly explained agents' preferences only in pairs with a low inconsistent response. Averaged response time positively correlated with H, confirming entropy as an indicator of choice difficulty. Group analyses on fMRI data revealed a cluster in the paracingulate cortex as the neural correlate of H. Besides, BOLD signal in the posterior cingulate correlated with the SV of the pair only in consistent decisions, confirming that SV loses its explanatory power on highly inconsistent decisions. Finally, the anterior and central cingulate were especially recruited when predicting a secured effortless reward, compared with a secured reward that involved a maximum effort. Our study shows that different regions of the cingulate cortex are involved in choice inconsistency, SV and processing effort costs.

Roles of Ventromedial Prefrontal Cortex and Anterior Cingulate in Subjective Valuation of Prospective Effort.

The perceived effort level of an action shapes everyday decisions. Despite the importance of these perceptions for decision-making, the behavioral and neural representations of the subjective cost of effort are not well understood. While a number of studies have implicated anterior cingulate cortex (ACC) in decisions about effort/reward trade-offs, none have experimentally isolated effort valuation from reward and choice difficulty, a function that is commonly ascribed to this region. We used functional magnetic resonance imaging to monitor brain activity while human participants engaged in uncertain choices for prospective physical effort. Our task was designed to examine effort-based decision-making in the absence of reward and separated from choice difficulty-allowing us to investigate the brain's role in effort valuation, independent of these other factors. Participants exhibited subjectivity in their decision-making, displaying increased sensitivity to changes in subjective effort as objective effort levels increased. Analysis of blood-oxygenation-level dependent activity revealed that the ventromedial prefrontal cortex (vmPFC) encoded the subjective valuation of prospective effort, and ACC activity was best described by choice difficulty. These results provide insight into the processes responsible for decision-making regarding effort, partly dissociating the roles of vmPFC and ACC in prospective valuation of effort and choice difficulty.

Functional MRI and delay discounting in patients infected with hepatitis C.

Hepatitis C virus-infected (HCV+) adults evidence increased rates of psychiatric and cognitive difficulties. This is the first study to use functional magnetic resonance imaging (fMRI) to examine brain activation in untreated HCV+ adults. To determine whether, relative to non-infected controls (CTLs), HCV+ adults exhibit differences in brain activation during a delay discounting task (DDT), a measure of one's tendency to choose smaller immediate rewards over larger delayed rewards-one aspect of impulsivity. Twenty adults with HCV and 26 CTLs completed an fMRI protocol during the DDT. Mixed effects regression analyses of hard versus easy trials of the DDT showed that, compared with CTLs, the HCV+ group exhibited less activation in the left lateral occipital gyrus, precuneus, and superior frontal gyrus. There were also significant interactive effects for hard-easy contrasts in the bilateral medial frontal gyrus, left insula, left precuneus, left inferior parietal lobule, and right temporal occipital gyrus; the CTL group evidenced a positive relationship between impulsivity and activation, while the HCV+ group exhibited a negative relationship. Within the HCV+ group, those with high viral load chose immediate rewards more often than those with low viral load, regardless of choice difficulty; those with low viral load chose immediate rewards more often on hard choices relative to easy choices. Results show that HCV+ patients exhibit greater impulsive behavior when presented with difficult choices, and impulsivity is negatively related to activation in regions important for cognitive control. Thus, interventions that decrease impulsive choice may be warranted with some HCV+ patients.

FARMERS’ WILLINGNESS TO INVEST IN NEW COOPERATIVE INSTRUMENTS: A CHOICE EXPERIMENT

ABSTRACTGlobalization of agricultural markets put pressures on producer cooperatives to invest in expansion and growth to safeguard their competitiveness. Availability of capital is limited if farmers do not have incentives to increase their capital contribution. Cooperative literature recognizes the residual rights, transferability, and the appreciation potential of the investment as the potential solutions for the problems that may impede cooperative investments. The objective of this study is to understand farmer preferences regarding investment attributes and the potential for attracting investment capital from members and non‐members. We employ a choice experiment method to test new cooperative investment instruments. The data consist of a questionnaire conducted with 406 Finnish dairy farmers. Random parameter latent class logit model is used in the estimation of the data. The results indicate that most of the respondents regard the new investment instruments positively. However, farmers prefer restricting ownership rights to members. Incentives for members to participate in financing cooperative growth could be designed with capital‐based residual rights, mechanisms for transferability and for the appreciation of firm value. Estimation that considered choice difficulty improved model fit, which highlights the need to address respondent burden also in future studies of hypothetical investments in order to produce unbiased estimates.

How Tradeoffs Shrink Attribute Hierarchy

Why do people sometimes struggle with decisions that once seemed relatively simple? This research suggests that comparing options leads people to lose sight of which decision attributes are important. Although the difference between important and unimportant attributes is often clear in the abstract, the act of making tradeoffs highlights what people must forgo on one attribute in exchange for a gain on another, which increases the perceived importance of trivial attributes in particular. This causes the variance in perceived importance across attributes to shrink, blurring the distinction between important and unimportant attributes. Four experiments demonstrate this phenomenon, explore the underlying mechanism, and show how it leads to increased choice difficulty and dissatisfaction with the choice experience.

Inequality signals in dorsolateral prefrontal cortex inform social preference models.

Humans typically display inequality aversion in social situations, which manifests itself as a preference for fairer distributions of resources. However, people differ in the degree to which they dislike being worse off [disadvantageous inequality (DI) aversion] or better off [advantageous inequality (AI) aversion] than others. Competing models explain such behavior by focusing on aversion to payoff differences, maximization of total payoff or reciprocity. Using functional near-infrared spectroscopy, we asked which of these theories could better explain dorsolateral prefrontal cortex (dlPFC) activity while participants accepted or punished fair vs unfair monetary transfers in an anonymous norm compliance task. We found that while all participants exhibited DI aversion, there were substantial differences in preferences for AI, which were strongly predicted by dlPFC activation. Model comparisons revealed that both punishment behavior and prefrontal activity were best explained by a model that allowed for AI seeking rather than imposing aversion. Moreover, enhancing this model by taking into account behavioral response times, as a proxy for choice difficulty, further improved model fits. Our data provide evidence that the dlPFC encodes subjective values of payoff inequality and that this representation is richer than envisaged by standard models of social preferences.

Is fairness intuitive? An experiment accounting for subjective utility differences under time pressure

Evidence from response time studies and time pressure experiments has led several authors to conclude that “fairness is intuitive”. In light of conflicting findings, we provide theoretical arguments showing under which conditions an increase in “fairness” due to time pressure indeed provides unambiguous evidence in favor of the “fairness is intuitive” hypothesis. Drawing on recent applications of the Drift Diffusion Model (Krajbich et al. in Nat Commun 6:7455, 2015a), we demonstrate how the subjective difficulty of making a choice affects decisions under time pressure and time delay, thereby making an unambiguous interpretation of time pressure effects contingent on the choice situation. To explore our theoretical considerations and to retest the “fairness is intuitive” hypothesis, we analyze choices in two-person binary dictator and prisoner’s dilemma games under time pressure or time delay. In addition, we manipulate the subjective difficulty of choosing the fair relative to the selfish option. Our main finding is that time pressure does not consistently promote fairness in situations where this would be predicted after accounting for choice difficulty. Hence, our results cast doubt on the hypothesis that “fairness is intuitive”.