How much Fear? Exploring the Role of Integral Emotions on Stated Preferences for Wildlife Conservation

Scientific evidence suggests that emotions affect actual human decision-making, particularly in highly emotionally situations such as human-wildlife interactions. In this study we assess the role of fear on preferences for wildlife conservation, using a discrete choice experiment. The sample was split into two treatment groups and a control. In the treatment groups the emotion of fear towards wildlife was manipulated using two different pictures of a wolf, one fearful and one reassuring, which were presented to respondents during the experiment. Results were different for the two treatments. The assurance treatment lead to higher preferences and willingness to pay for the wolf, compared to the fear treatment and the control, for several population sizes. On the other hand, the impact of the fear treatment was lower than expected and only significant for large populations of wolves, in excess of 50 specimen. Overall, the study suggests that emotional choices may represent a source of concern for the assessment of stable preferences. The impact of emotional choices is likely to be greater in situations where a wildlife-related topic is highly emphasized, positively or negatively, by social networks, mass media, and opinion leaders. When stated preferences towards wildlife are affected by the emotional state of fear due to contextual external stimuli, welfare analysis does not reflect stable individual preferences and may lead to sub-optimal conservation policies. Therefore, while more research is recommended for a more accurate assessment, it is advised to control the decision context during surveys for potential emotional choices.

Mind the Gap! Reconciling Environmental Water Requirements with Scarcity in the Murray–Darling Basin, Australia

The Murray–Darling Basin Plan is a $AU 13 billion program to return water from irrigation use to the environment. Central to the success of the Plan, commenced in 2012, is the implementation of an Environmentally Sustainable Level of Take (ESLT) and a Sustainable Diversion Limit (SDL) on the volume of water that can be taken for consumptive use. Under the enabling legislation, the Water Act (2007), the ESLT and SDL must be set by the “best available science.” In 2009, the volume of water to maintain wetlands and rivers of the Basin was estimated at 3000–7600 GL per year. Since then, there has been a steady step-down in this volume to 2075 GL year due to repeated policy adjustments, including “supply measures projects,” building of infrastructure to obtain the same environmental outcomes with less water. Since implementation of the Plan, return of water to the environment is falling far short of targets. The gap between the volume required to maintain wetlands and rivers and what is available is increasing with climate change and other risks, but the Plan makes no direct allowance for climate change. We present policy options that address the need to adapt to less water and re-frame the decision context from contestation between water for irrigation versus the environment. Options include best use of water for adaptation and structural adjustment packages for irrigation communities integrated with environmental triage of those wetlands likely to transition to dryland ecosystems under climate change.

How to de-bias investment judgements–unpacking bias and possible remedies in a capital investment context

PurposeResearch on biases in investment decision-making is indubitably important; however, studies in this context are relatively scarce. Unpacking bias has received attention in the psychological literature yet very little attention from management accounting research. This bias suggests that the perceived probability that an event will occur generally increases when the event's description is unpacked into a disjunction of subevents. The authors hypothesize that for a capital investment decision context, managers' judgement of the probability of a future event depends on whether the event is described as one packed event or is unpacked into several disjoint subevents. Additionally, the authors propose that altering the format of the description of an event's occurrence from percentage values to relative frequencies reduces unpacking bias.Design/methodology/approachTo test the study’s hypotheses, the authors conducted two experiments based on a 3 × 2 mixed experimental design in which manager participants were asked to estimate the failure probabilities of technical systems in the context of an investment decision.FindingsThe authors provide evidence that unpacking bias occurs in an investment scenario, which can be characterized as a high-stakes decision context. Changing the format in which probabilities are presented from percentage values to relative frequencies significantly reduces the bias.Research limitations/implicationsAdditional instructions did not further reduce unpacking bias.Practical implicationsFor investment decisions under uncertainty, performance indicators in management templates should be presented in relative frequencies to improve managerial decision-making. The fact that the authors could not show an additional effect of instructions in management accounting reports indicates that it is challenging for management accountants to reduce the biased decision-making of managers by “teaching” them through the provision of instructions.Originality/valueThe authors contribute to accounting research by illustrating unpacking bias and by deriving a debiasing mechanism in a capital investment decision context.

Egocentric Projection is a Rational Strategy for Accurate Emotion Prediction

People need to accurately understand and predict others’ emotions in order to build and maintain meaningful social connections. However, when they encounter new social partners, people often do not have enough information about them to make accurate inferences. Rather, they often resort to an egocentric heuristic, and make predictions about a target by using their own self-knowledge as a proxy. Is this egocentric heuristic a form of cognitive bias, or is it a rational strategy for real-world social prediction? If egocentrism provides a rational and effective solution to the challenging task of social prediction in naturalistic contexts, we should expect that a) egocentric predictions tend to be more accurate, and b) people rely on self-knowledge to a greater extent when it’s more likely to be a good proxy. Using an emotion prediction task and personality measures, we assessed similarity and predictive accuracy between first year college students and their new acquaintance roommate. Results demonstrated that, when people need to make predict an unfamiliar target’s emotions, self-knowledge can often effectively approximate knowledge about others, and thus support accurate predictions. Moreover, participants that were typical of the sample, whose self-knowledge can better approximate information about the target, relied more on self-knowledge in their predictions, and thus achieved higher accuracy. These findings suggest that people rationally tune their use of egocentrism based on whether it is likely to pay off. Overall, these findings demonstrate a rational side to a cognitive phenomenon usually framed as a cognitive pitfall, namely egocentric projection, when its natural decision context is taken into consideration.

Speed-accuracy tradeoffs in decision making: Perception shifts and goal activation bias decision thresholds

A fundamental aspect of decision making is the speed-accuracy tradeoff (SAT): slower decisions tend to be more accurate, but since time is a scarce resource people prefer to conclude decisions more quickly. The current research adds to the SAT literature by documenting two previously unrecognized influences on the SAT: perception shifts and goal activation. Decision makers' perceptions of what constitutes a fast or a slow decision, and what constitutes an accurate or inaccurate decision, are based on prior experience, and these perceptions influence decision speed. Similarly, previous experience in a decision context associates the context with a particular decision goal. Thus, in later decisions the decision context will activate this goal, and thereby influence decision speed. Both of these mechanisms contribute to a specific decision bias: decision speeds are biased toward original decision speeds in a decision context. Four experiments provide evidence for the bias and the two contributing mechanisms.

How Power Influences Decision-Makers’ Investment Behavior in the Domains of Loss and Gain

We present a study (N = 645) investigating how power alters people’s propensity to take investment risks in a changing decision context of gains and losses and the intensity of their reactions to this experience. The results indicate that people in a state of power made more risky investment decisions than the control group regardless of prior gain or loss outcome, whereas people lacking power took less investment risk than the control group, regardless of previous outcomes. Moreover, people with power and those lacking power differed in their reactions to gains and losses, with the former reacting more to gains and the latter to losses.

Simple deterministic and complex probabilistic regularities underlying risky choices are acquired in a changing decision context

Beliefs about positive and negative outcome probabilities have been frequently investigated in experience-based risky decision making. However, it has not been clarified how these beliefs emerge and whether they remain persistent if the predictability and complexity of outcome probabilities change across decision contexts. Hence, the present study manipulated these two factors in a variant of the Balloon Analogue Risk Task performed by healthy young adults. In the first and final task phases, outcomes (rewards or balloon bursts) were predictable because of the presence of an underlying regularity. In the middle phase, outcomes were unpredictable because the regularity was absent. The complexity of the regularity differed across the deterministic, probabilistic, and hybrid experimental conditions. In the simple deterministic condition, a repeating sequence of three deterministic regularities perfectly predicted balloon bursts. In the more complex probabilistic condition, a single probabilistic regularity ensured that the probability of balloon bursts increased with each successive pump. In the most complex hybrid condition, a repeating sequence of three different probabilistic regularities increased burst probabilities. Even without informing participants about the presence or absence of the regularity, sensitivity to both the simple deterministic and the most complex hybrid regularities emerged and influenced risk taking. Unpredictable outcomes of the middle phase did not deteriorate the acquired sensitivity to these regularities. When only a single probabilistic regularity was present, predictable and unpredictable outcomes were processed similarly. In conclusion, assuming the reappearance of the initially experienced regularity, the robustness of representations might serve fast adaptation in a volatile decision environment.

Behavioral Economics in Plea-Bargain Decision-Making: Beyond the Shadow-of-Trial Model

Legal scholars have long assumed that plea bargains are contracts negotiated between rational actors who adhere to the dictates of the normative shadow-of-trial model. The two key features that rational actors presumably haggle over in the shadow of trial are the criminal charge (and associated sentence) and the probability of trial conviction. The behavioral economics theory of discounting, however, offers a theoretical foundation for testing the shadow-of-trial model. This article summarizes findings from experimental discounting studies in behavioral economics and psychological science – showing that these paradigms can be successfully applied to the plea-bargaining decision context wherein the likelihood of trial is uncertain and delayed, and the plea bargain is relatively certain and immediate. We suggest that the implications of applying discounting to plea bargaining are three-fold: (1) empirical evidence suggests that the shadow-of-trial model is too narrow; (2) the discounting of non-monetary losses may involve slightly different psychological processes than contexts involving monetary outcomes; and (3) probability of conviction and delay until trial constitute situational features that elicit guilty pleas despite a defendant’s factual innocence.

How good is good enough? Quantifying the impact of benefits, accuracy, and privacy on willingness to adopt COVID-19 decision aids

An increasing number of data-driven decision aids are being developed to provide humans with advice to improve decision-making around important issues such as personal health and criminal justice. For algorithmic systems to support human decision-making effectively, people must be willing to use them. We expand upon prior research by empirically modeling how accuracy and privacy influence intent to adopt algorithmic systems, focusing on an globally-relevant decision context with tangible consequences: the COVID-19 pandemic. We analyze surveys of 4,615 Americans to (1) evaluate the effect of both accuracy and privacy concerns on reported willingness to install COVID-19 apps; (2) examine how different groups of users weigh accuracy relative to privacy; and (3) we empirically develop the first statistical models, to our knowledge, of how the amount of benefit (e.g., error rate) and degree of privacy risk in a data-driven decision aid may influence willingness to adopt.

Valences and sense of personal autonomy with regard to professional development in Dutch primary teachers: Do decision contexts and age make a difference?

In this study on motivations concerning professional development (PD) we interviewed 95 primary school teachers in the Netherlands. We coded these data using the Unified Model of Task-specific Motivation (de Brabander & Martens, 2014) in different decision contexts concerning who decides about teacher participation in PD: school board, teacher teams, or individual teachers. We analysed the valences that teachers associated with PD activities, their experiences of autonomy, and whether and how these variables were affected by decision context and teacher age. Results show that decision contexts relate differently to valences and autonomy experiences. Positive autonomy and positive valences increased going from schoolboard to team to individual decision contexts. Whereas the literature on effective teacher PD stresses the importance of PD design features, our study is the first to empirically demonstrate the crucial influence of decision contexts. Among older teachers, teaching experience informed the selection of PD content to transfer to their classrooms. Younger teachers tended to first explore whether PD worked in their classrooms before deciding about adoption. Direct applicability emerged as a dominant criterion for evaluating PD. Decision context and autonomy regarding PD programmes play important roles in ensuring applicability. Our research revealed that the dominance of the direct applicability criterion was not motivated by student benefits alone. It was also based in an attitude of efficiency among primary teachers, reflecting growing work pressures and a general prioritisation of classroom teaching above all other tasks, including PD.