Certainty Effect Research Articles

Bounded subadditivity in management decisions

PurposeAs subjects irrationally perceive probability changes as more impactful when shifting an event from impossible to possible or from possible to certain, compared to increasing the likelihood of an already possible event, this study examines how workers process success probabilities and whether their resource allocation decisions are distorted by bounded subadditivity.Design/methodology/approachWe conduct an online randomized experiment with 3,980 employees.FindingsWe detect a certainty effect (upper subadditivity), whereby professionals are willing to devote a disproportionate number of hours to a project when their contribution transforms the success of the initiative from possible to certain rather than increasing the likelihood of success by the same percentage points. We find no evidence of the possibility effect (lower subadditivity), whereby workers would devote a disproportionate effort when their contribution turns a sure failure into a possible success rather than simply increasing the likelihood of success by the same percentage points. We observe a rational tendency to try harder for a greater increase in the probability of success, but only far from the limits of the probability spectrum and not close to the limits.Originality/valueAttempts to understand bounded subadditivity in management decisions have been incomplete. We disentangle two real-world variables and offer a more refined operationalization.

The Zero Effect: An Eye‐Tracking Study of Affect and Motivation in Risky Choices

ABSTRACTDecision makers often prefer safe wins over risky gambles, even if the latter promise higher payoffs than the former. One mechanism that explains this choice pattern is the certainty effect, whereby probabilities of 0 and 1 are interpreted accurately but intermediate probabilities are distorted by diminishing sensitivity. We tested an alternative explanation that was recently proposed, the idea that people would be motivated by avoiding zero outcomes rather than being attracted to sure gains. This zero‐outcome aversion in gain‐domain choices was called the zero effect. By analogy, we proposed that decision makers would approach zero outcomes in the loss domain. Two eye‐tracking experiments investigated visual attention as a key component of the zero effect in the gain domain (Experiment 1) and the loss domain (Experiment 2). Choices were consistent with the zero effect. In the gain domain, gambles were chosen less frequently if they included a zero outcome. In contrast, zero‐outcome gambles were chosen more frequently in the loss domain. Eye movements and pupillometry indicated that zero outcomes in both domains (a) were less frequently fixated than other outcomes and (b) were associated with increased arousal. We concluded that domain‐specific affective responses to zero outcomes aligned with approach/avoidance motivation. These distinct motivations in turn biased information search and choice behavior.

Theoretical foundations for the development of criteria for evaluating audience preferences in modern cinema

The purpose of the article is to highlight the theoretical foundations for the development of criteria for evaluating audience preferences in modern cinema. The research methodology is based on theoretical analysis, synthesis and generalization of scientific sources on the research topic, and the comparative method. The novelty of the research lies in the fact that the author highlights the theoretical foundations of the methodology of criteria and variables for assessing the success and demand of modern films as a foundation for testing and developing a questionnaire to identify audience preferences. As a conclusion, the authors states that there is a need to pay attention to the phenomena of audience choice (for example, the "certainty effect", etc.); "flow experience" within the stage of watching a movie for its emotional perception by the audience. Considering the issues of statistics, assessment of the potential commercial success of a film production and the complex of factors affecting it, it is advisable to cite D. Kahneman's position. This researcher provides an argument for the value of simple formulas for forecasting, operating with a low number of basic criteria. Thus, this author emphasizes the importance of formulas that provide equal weight for each predictive factor, which is due to their indifference to the randomness associated with the organization of the sample. In the context of the statistics of the film business sector, the corresponding hypothesis will look like this: a model for evaluating the future success of projects in certain genres is able to provide a higher level of reliability compared to models that ignore genre originality. Thus, in the study of methods for predicting the commercial success of films, carried out by A.S. Tatarnikov, the great reliability of the predictive model using information on paintings of certain genres of entertainment (in particular, adventure films, comedies, etc.) was confirmed.

Analysis Of Possible Influencing Factors and Forecasting the Concentration of PM2.5

Air quality is an important factor that affects the quality of people’s lives. With the development of the times, people’s health awareness is increasing. To truly enhance the well-being of all mankind, the author wants to figure out possible influencing factors of PM2.5 and forecast the concentration of it. The author gathers data from 2015 to 2023 and uses 4 different ways in analyzing influencing factors, then the author applies ARIMA model and LSTM model in forecasting. The author finds out that O3, precipitation, average 2-minute wind speed, and average relative humidity are nearly irrelevant to PM2.5 concentration; average air pressure and average temperature have no certainty effect on PM2.5 concentration; PM10, SO2, NO2, CO have a greater impact on PM2.5 concentration, and they are all positively correlated. As for forecasting models, LSTM model is better when performing long-step forecasts while ARIMA model is more accurate when performing short-step forecasts. These conclusions can be used by governments when forecasting relative parameters and they can take more accurate actions in dealing with PM2.5 pollution with the given influencing factors and their magnitudes.

False certainty as an unwanted side effect of knowledge acquisition in computer-based online search and content learning

Previous research has shown that learners’ subjective certainty in the assumed correctness of their false answers to a knowledge test increased after online learning. It is unclear, however, 1) whether this False Certainty Effect (FaCE) results from online learning per se, or 2) whether a FaCE results from people confusing their own knowledge with information available on the internet while searching the internet, and 3) whether any topic-directed activity can result in a FaCE, even if it is not obviously topic related. We conducted two computer-based experiments to answer these questions. In Experiment 1, participants (N = 135) were randomly assigned to either an online-search learning condition, a computer-based content-learning condition with pre-selected learning material, or a computer-based topic-exploration condition with no learning-relevant information. Across all conditions, there was an increase in false certainty after the activity. The FaCE was equally strong in the two learning conditions (online search and content learning) and minimal in the non-learning condition. In Experiment 2 (N = 87), we replicated the FaCE for a learning activity with pre-selected materials but did not find a spill-over effect to an unrelated topic. These results indicate that the FaCE is primarily an unwanted side effect of the knowledge acquisition that arises from brief computer-based learning activities.

Differences in decisions affected by cognitive biases: examining human values, need for cognition, and numeracy

A better understanding of factors that can affect preferences and choices may contribute to more accurate decision-making. Several studies have investigated the effects of cognitive biases on decision-making and their relationship with cognitive abilities and thinking dispositions. While studies on behaviour, attitude, personality, and health worries have examined their relationship with human values, research on cognitive bias has not investigated its relationship to individual differences in human values. The purpose of this study was to explore individual differences in biased choices, examining the relationships of the human values self-direction, conformity, power, and universalism with the anchoring effect, the framing effect, the certainty effect, and the outcome bias, as well as the mediation of need for cognition and the moderation of numeracy in these relationships. We measured individual differences and within-participant effects with an online questionnaire completed by 409 Brazilian participants, with an age range from 18 to 80 years, 56.7% female, and 43.3% male. The cognitive biases studied consistently influenced choices and preferences. However, the biases showed distinct relationships with the individual differences investigated, indicating the involvement of diverse psychological mechanisms. For example, people who value more self-direction were less affected only by anchoring. Hence, people more susceptible to one bias were not similarly susceptible to another. This can help in research on how to weaken or strengthen cognitive biases and heuristics.

The Impact of (In)Stability of Pension System on Retirement Timing: Macro-Level Analysis Based on “Certainty Effect”

Abstract Retirement timing is an issue of great political importance these days. Policy-makers develop various initiatives encouraging workers to postpone retirement beyond the statutory retirement age. This effort brings, however, just minimal outcomes. Although increasing opportunities and abilities to work in old age, in some countries people tend to retire as soon as it is possible. In economic terms, they make suboptimal (irrational) decisions.

Behavioral economics and monetary wisdom: A cross‐level analysis of monetary aspiration, pay (dis)satisfaction, risk perception, and corruption in 32 nations

AbstractCorruption involves greed, money, and risky decision‐making. We explore the love of money, pay satisfaction, probability of risk, and dishonesty across cultures. Avaricious monetary aspiration breeds unethicality. Prospect theory frames decisions in the gains‐losses domain and high‐low probability. Pay dissatisfaction (in the losses domain) incites dishonesty in the name of justice at the individual level. The Corruption Perceptions Index, CPI, signals a high‐low probability of getting caught for dishonesty at the country level. We theorize that decision‐makers adopt avaricious love‐of‐money aspiration as a lens and frame dishonesty in the gains‐losses domain (pay satisfaction‐dissatisfaction, Level 1) and high‐low probability (CPI, Level 2) to maximize expected utility and ultimate serenity. We challenge the myth: Pay satisfaction mitigates dishonesty across nations consistently. Based on 6500 managers in 32 countries, our cross‐level three‐dimensional visualization offers the following discoveries. Under high aspiration conditions, pay dissatisfaction excites the highest‐ (third‐highest) avaricious justice‐seeking dishonesty in high (medium) CPI nations, supporting the certainty effect. However, pay satisfaction provokes the second‐highest avaricious opportunity‐seizing dishonesty in low CPI entities, sustaining the possibility effect—maximizing expected utility. Under low aspiration conditions, high pay satisfaction consistently leads to low dishonesty, demonstrating risk aversion—achieving ultimate serenity. We expand prospect theory from a micro and individual‐level theory to a cross‐level theory of monetary wisdom across 32 nations. We enhance the S‐shaped Curve to three 3‐D corruption surfaces across three levels of the global economic pyramid, providing novel insights into behavioral economics, business ethics, the environment, and responsibility.

Identification Problems in Probabilistic Measures of Perceived Arrest Risk: Estimating a Partially-Identified Certainty Effect

Identification Problems in Probabilistic Measures of Perceived Arrest Risk: Estimating a Partially-Identified Certainty Effect

Gaining a deeper understanding of the psychology underpinning significance judgements in environmental impact assessment (EIA)

ABSTRACT Significance judgements lie at the heart of EIA and provide the basis and justification for overall decision-making. Although the subjective nature of significance judgements is widely recognized, there has been limited research aimed at gaining a deeper understanding of its implications. This paper builds on the growing tradition of exploring learning from psychology in dealing with challenges in EIA practice, in this case, significance judgements. The aim of this research is therefore, to gain a deeper understanding of the psychology underpinning significance judgements. This is achieved by applying 10 concepts from psychology to the four steps in the ‘significance spectrum model’, namely: decide thresholds, make predictions, judge acceptability and consider mitigation. The results suggest that significance judgements should (with underpinning concepts from psychology provided in parentheses) aim for a limited number of key thresholds (paradox of choice); design thresholds with future gains in mind (loss aversion), reconsider probability scoring (possibility and certainty effect); avoid judgements based on limited information (What You See Is All There Is, WHYSIATI); utilise statistical prediction over expert opinion (expert fallacy); communicate carefully (priming, framing and cognitive ease); and consider personal attitudes and biases (affect heuristic).

Regional freezing index and its frequency calculation considering the certainty effects of elevation and latitude

The freezing index (FI) is an important index used in investigations of climate change, frozen ground degradation and frost heave resistance engineering design. In view of the fact that the deterministic effects of latitude and elevation are not considered in the frequency calculation of FI, we proposed an index-freezing method that considers the certainty effects of both elevation and latitude by referring to the index-flood method in this paper. The correlations between the FI and certainty factors (elevation and latitude) were obtained by multiple regression analysis. The effects of latitude and elevation were then removed by nondimensionalisation, and dimensionless FI sequences were subsequently obtained. Finally, the index-freezing method was verified by regional probability analysis. Using the daily average temperature data recorded at 10 major meteorological stations over the 1960–2020 period in Ningxia, the calculation process of the FI and its frequency distribution were provided. The results showed that the proposed FI method can not only remove the certainty effects of elevation and latitude but can also consider the uncertainty associated with interannual FI variations, thus providing more scientific, reasonable and accurate results. The generalised extreme value (GEV) distribution is the optimal frequency distribution of the nondimensional regional FI. The estimation errors of the missing data tests were mostly within 10%, and the residual sum of squares (RSS) and root-mean-square error (RMSE) values were also lower than those obtained through spatial interpolation, thus indicating that the interpolation precision of the proposed FI method was optimal.

A Study on Choices and the Profile of the Brazilian Investor in the Decision-Making Process

The objective of this work was to show, through Prospect Theory (PT), a broader approach to finance and economics, which includes concepts of psychology and sociology, how agents, and particularly investors, are susceptible to deviations from rationality that directly impact their choices, making their decisions not always by the pillars that support classical theories of finance. The research was 382 Brazilian investors. Through the questionnaire, it is observed how much a behavioral effect dramatically influences the choices of economic agents who are mostly men and ill-prepared academically. One of the important verifications found evaluating the answers of the 382 interviewees was about the investors' reaction; in case of a loss, we have that the interviewees prefer probable losses to the detriment of certain losses, even if smaller, and this fact helps to eliminate any explanation that can be given to the certainty effect in the sense that the aversion to volatility. More than 68% when answering some of the questions violated the precepts of the Expected Utility Theory. People opted for the answer with a positive and more significant standard deviation, demonstrating that they are not risk averse. When the certainty of the result increases, the choice for assets with smaller standard deviation increases; in this case, we have evidence of a reduction in risk aversion.

The Certainty Effect for Gains and Losses Emerges in Joint Evaluation but Not Always in Separate Evaluation

Abstract Six studies investigated people's attitudes toward uncertainty. Participants rated the attractiveness of pairs of gambles in either a gain or a loss frame. We varied the level of uncertainty, the monetary outcomes, and the evaluation mode of the gambles (i.e., joint versus separate evaluation). Experiments 1a and 1b compared a sure gain (loss) to a risky gain (loss), with both gambles having identical expected value. Experiments 2a and 2b included an almost sure (i.e., 98%) gain (loss) and risky gain (loss). When gambles entailed gains, a risky gamble became less attractive when evaluated in joint than in separate evaluation. The opposite pattern emerged when gambles entailed losses. The difference between a risky and a sure (or almost sure) gamble was weaker (or eliminated) in separate evaluation. Experiments 3a and 3b presented a risky gamble alone or with other gambles with varying probability and outcomes to be gained or lost. When gambles entailed gains (losses), a risky gamble became less (more) attractive and was chosen less (more) frequently when paired with gambles offering a higher probability of gaining (losing) smaller amounts. Overall, affective reactions and preferences for uncertain gambles depend on the decision context, and the certainty effect can disappear in separate evaluation.

Nonlinear probability weighting can reflect attentional biases in sequential sampling.

Nonlinear probability weighting allows cumulative prospect theory (CPT) to account for key phenomena in decision making under risk (e.g., certainty effect, fourfold pattern of risk attitudes). It describes the impact of risky outcomes on preferences in terms of a rank-dependent nonlinear transformation of their objective probabilities. The attentional Drift Diffusion Model (aDDM) formalizes the finding that attentional biases toward an option can shape preferences within a sequential sampling process. Here we link these two influential frameworks. We used the aDDM to simulate choices between two options while systematically varying the strength of attentional biases to either option. The resulting choices were modeled with CPT. Changes in preference due to attentional biases in the aDDM were reflected in highly systematic signatures in the parameters of CPT's weighting function (curvature, elevation). In a re-analysis of a large set of previously published data, we demonstrate that attentional biases are also empirically linked to patterns in probability weighting as suggested by the simulations. Our analyses also revealed a previously overlooked link between patterns in probability weighting and response times. These findings highlight that distortions in probability weighting can arise from simple option-specific attentional biases in information search, and suggest an alternative to common interpretations of weighting-function parameters in terms of probability sensitivity and optimism. They also point to novel, attention-based explanations for empirical phenomena associated with characteristic shapes of CPT's probability-weighting function (e.g., certainty effect, description-experience gap). The results advance the integration of two prominent computational frameworks for decision making. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Interventions for increasing immunosuppressant medication adherence in solid organ transplant recipients.

Interventions for increasing immunosuppressant medication adherence in solid organ transplant recipients.

A study on stock market investors during COVID phase – prospect theory approach

At the macro-level, behavioral finance challenges classic financial theories. It shows that investor behavior in the real world is incompatible with the fundamental assumption of rationality in traditional finance, as studied by Sedaghati. While taking decisions, including financial decisions, rational thoughts are not involved, as suggested by modern theory. Additionally, these decisions are taken by them are also often inconsistent. Contrarily, human decisions are subject to several irrational principles, as in an evaluator study by Kannadhasan. These decisions are taken by considering the risks and returns involved. Prospect theory is one of the many theories derived from behavioral finance was first invented in a 1979 paper by Daniel Kahneman and Amos Tversky. It is commonly seen as the best explanation of how people evaluate risk in experimental settings, as researched by Barberis. This theory mainly includes how individuals or groups of investors decide between the alternatives under the umbrella of risk and uncertainty. This research evaluates the stock investors’ behaviors during the COVID-19 phase in India using prospect theory; many factors affect the decision of stock investors, such as loss aversion, risk aversion, certainty effect, reflective effect, etc., observed by Kahneman & Tversky. This study explores the possibility of factors of prospect theory on investors’ decisions about their investments during the COVID-19 phase. The results provide insights into how individual investors’ decisions vary during this pandemic situation.

Chance theory: A separation of riskless and risky utility

In a temporal context, sure outcomes may yield higher utility than risky ones as they are available for the execution of plans before the resolution of uncertainty. By observing a disproportionate preference for certainty, empirical research points to a fundamental difference between riskless and risky utility. Chance Theory (CT) accounts for this difference and, in contrast to earlier approaches to separate risky and riskless utility, does not violate basic rationality principles like first-order stochastic dominance or transitivity. CT evaluates the lowest outcome of an act with the riskless utility v and the increments over that outcome, called chances, by subjective expected utility (EU) with a risky utility u. As a consequence of treating sure outcomes differently to risky ones, CT is able to explain the EU-paradoxes of Allais (Econometrica, 21(4): 503–546, 1953) that rely on the certainty effect, and also the critique to EU put forward by Rabin (Econometrica, 68(5): 1281–1292, 2000). Moreover, CT separates risk attitudes in the strong sense, captured entirely by u, from attitude towards wealth reflected solely through the curvature ofv.

Leveraging Systematic Reviews to Explore Disease Burden and Costs of Per- and Polyfluoroalkyl Substance Exposures in the United States

Accelerating evidence confirms the contribution of per- and polyfluoroalkyl substances (PFAS) to disease burden and disability across the lifespan. Given that policy makers raise the high cost of remediation and of substituting PFAS with safer alternatives in consumer products as barriers to confronting adverse health outcomes associated with PFAS exposure, it is important to document the costs of inaction even in the presence of uncertainty. We therefore quantified disease burdens and related economic costs due to legacy PFAS exposures in the US in 2018. We leveraged systematic reviews and used meta-analytic inputs whenever possible, identified previously published exposure–response relationships, and calculated PFOA- and PFOS-attributable increases in 13 conditions. These increments were then applied to census data to determine total annual PFOA- and PFOS-attributable cases of disease, from which we calculated economic costs due to medical care and lost productivity using previously published cost-of-illness data. We identified PFAS-attributable disease costs in the US of $5.52 billion across five primary disease endpoints shown to be associated with PFAS exposure in meta-analyses. This estimate represented the lower bound, with sensitivity analyses revealing as much as $62.6 billion in overall costs. While further work is needed to assess probability of causation and establish with greater certainty effects of the broader category of PFAS, the results confirm further that public health and policy interventions are still necessary to reduce exposure to PFOA and PFOS and their endocrine-disrupting effects. This study demonstrates the large potential economic implications of regulatory inaction.

The normalized expected utility – entropy and variance model for decisions under risk

The normalized expected utility - entropy and variance (NEU-EV) decision model and associated risk measure are proposed for the analysis and modelling of decisions under risk. The model depends on normalized entropy and variance and expected utility, can be applied to decision problems depending on actions, where the states have different numbers of outcomes. Several properties of risk perception and examples of certainty effects, common ratio effects and common consequence effects are analysed using this model, considering actions with non-negative outcomes. The results show that the NEU-EV model is an adequate model for explaining these risk decision problems.

Stick or carrot for traffic demand management? Evidence from experimental economics

The debate between stick (penalties) and carrot (rewards) strategies has been widely carried out in various academic realms, including transportation. This paper seeks to compare the instantaneous and longitudinal effectiveness of a traditional penalty-based congestion pricing strategy and an innovative Incentive-Based Traffic Demand Management (IBTDM) strategy using an online interactive laboratory experiment focused on departure time choice. We also investigate the social-economic phenomena of loss aversion and risk aversion. The experimental results show that penalties and rewards can both positively induce sustainable travel behavior. The stronger demand-shifting performance of the penalty-based strategy at first demonstrates that ‘loss aversion’ does exist in TDM, at least initially. However, this loss aversion weakens as the experiment continues, which verifies the myopic loss aversion theory. Moreover, risky decision-making in the gambling games proves the existence of risk seeking, which violates the ‘certainty effect’. To overcome the disadvantage of laboratory experiment that participants need to accomplish the experiment all in once for considerably long time, an agent-based model is calibrated based on real participants’ behavior to further verify the long-term effectiveness of penalties and rewards, and to verify the effectiveness of other optimized penalty/reward schemes. The simulated results based on the agent-based model indicate that the theoretical optimal penalty scheme performs better in general in congestion alleviation, while a more reasonable reward scheme that considers psychological factors can achieve the same effectiveness in terms of total system travel time reduction. The findings of this research can be used to guide the design of TDM strategies, and the behavioral data collection approach based on our laboratory experiment is portable for future studies.