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.

EMBEDDED REMOTE GROUP ENVIRONMENT THROUGH MODIFICATION IN MACBETH – AN APPLICATION OF CONTRACTOR’S SELECTION IN CONSTRUCTION

A group decision environment has profound roots in MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) analysis which indeed has plentiful advantages; however, many researchers envisage the embedded group decision system as an impediment in actual implementation. The accessibility of explicit interaction of decision makers at a single platform in the form of embedded group decision environment is a great impediment to the researchers. Accordingly, this research aims to tailor a novel alternative system of dealing with the embedded group decision under a remote group decision environment via integrating MACBETH and Exploratory Factor Analysis. The study finds that an embedded remote group decision making system could serve as an alternative system of group decision making which has plentiful perks in group decision applications. This system could help researchers to carry out research without confusing in embedded group decision environment but including all decision-makers in the model. The implication of proposed system is not only limited to MACBETH; however, due to system’s versatility, a similar approach could be fruitful for other group-related environments involving collective decisions.

Complexity Aversion in Risky Choices and Valuations: Moderators and Possible Causes

In the age of digitalization and globalization, our decision environments have become increasingly complex. However, it remains unclear under what circumstances complexity affects risk taking. In two experiments (one with a representative sample), we go beyond the behavioral effects and provide a cognitive explanation for the impact of complexity on risk taking. Results show that complexity, defined as the number of outcomes of a risky lottery, decreased choice propensity in choices between two lotteries but had a smaller effect on valuations of individual lotteries. Importantly, participants who spent less time looking at the complex option in choices, were less affected by complexity. Thus, a dislike of cognitive effort can explain the effect of complexity and the difference between choice and valuation. The small effect of complexity on valuations could be explained by individual differences in cognitive ability. Together, we showed that the decision environment as well as individual differences affected the impact of complexity on risk taking and we discuss cognitive explanations for these phenomena.

Confidence in complex risk judgments: the roles of uncertainty, experience, and affect

Disagreement persists about the origin of confidence and the internal signals that influence its formation. Using combined individual participant data from four studies (N = 181), we examined confidence in relation to the perceived source of uncertainty for a risk judgment and explored the roles of domain-specific experience and affective evaluations in the formation of confidence. In each study, participants with domain-specific experience (backcountry skiers) performed complex risk judgments (judging avalanche risk) for multiple highly uncertain contexts (hypothetical scenarios in avalanche terrain). We examined whether more experienced participants could better recognize the inherent uncertainty of the decision environment, and if they did so with greater confidence. For complex tasks such as judging avalanche risk, experience should increase a person’s understanding of the probabilistic, unpredictable nature of that environment. Yet our findings suggests that participants of all levels of experience attributed uncertainty to their own judgment process rather than to the limitations and inherent uncertainty of the environment. We also examined whether participants’ affective evaluations influenced confidence in their risk judgments. Affective evaluations are understood to play a crucial orienting role in the risk judgment process. We found evidence of an interplay between affective and cognitive judgments in the formation of confidence. Participants were more confident when their affective evaluation matched their risk judgment, and less confident when there was a mismatch between the two. Our research illustrates a troubling limitation in the development of confidence with experience and the potential (dis)advantageous effect of affective evaluations on confidence in certain contexts.

Adaptation to recent outcomes attenuates the lasting effect of initial experience on risky decisions

Both primarily and recently encountered information have been shown to influence experience-based risky decision making. The primacy effect predicts that initial experience will influence later choices even if outcome probabilities change and reward is ultimately more or less sparse than primarily experienced. However, it has not been investigated whether extended initial experience would induce a more profound primacy effect upon risky choices than brief experience. Therefore, the present study tested in two experiments whether young adults adjusted their risk-taking behavior in the Balloon Analogue Risk Task after an unsignaled and unexpected change point. The change point separated early “good luck” or “bad luck” trials from subsequent ones. While mostly positive (more reward) or mostly negative (no reward) events characterized the early trials, subsequent trials were unbiased. In Experiment 1, the change point occurred after one-sixth or one-third of the trials (brief vs. extended experience) without intermittence, whereas in Experiment 2, it occurred between separate task phases. In Experiment 1, if negative events characterized the early trials, after the change point, risk-taking behavior increased as compared with the early trials. Conversely, if positive events characterized the early trials, risk-taking behavior decreased after the change point. Although the adjustment of risk-taking behavior occurred due to integrating recent experiences, the impact of initial experience was simultaneously observed. The length of initial experience did not reliably influence the adjustment of behavior. In Experiment 2, participants became more prone to take risks as the task progressed, indicating that the impact of initial experience could be overcome. Altogether, we suggest that initial beliefs about outcome probabilities can be updated by recent experiences to adapt to the continuously changing decision environment.

Overview

This chapter characterizes production in a dynamic decision-making environment. The classic characterization of static firm decision making is contrasted with the dynamic decision environment where not all inputs are freely adjusted. The latter characterization is motivated by the conjecture that transaction costs are associated with adjusting the capital stock at a rapid rate per unit of time and these costs increase rapidly with the absolute rate of investment. In fact, these costs increase so rapidly that the firm may never attempt to achieve a jump in its capital stock at any given moment. Such transaction (or adjustment) costs have implications for the nature of the technology. This interplay is introduced in this chapter and serves as a foundation for the dynamic structure that follows throughout the book.

A method for robust design in a coupled decision environment

The design of a connected engineered system requires numerous design decisions that influence one another. In a connected system that comprises numerous interacting decisions involving concurrency and hierarchy, accounting for interactions while also managing uncertainties, it is imperative to make robust decisions. In this article, we present a method for robust design using coupled decisions to identify design decisions that are relatively insensitive to uncertainties. To account for the influence among decisions, design decisions are modelled as coupled decisions. They are defined using three criteria: the types of decisions, the strength of interactions and the decision levels. In order to make robust decisions, robust design methods are classified based on sources of uncertainty, namely, Type I (noise factors), Type II (design variables) and Type III (function relationship between design variables and responses). The design of a one-stage reduction gearbox is used as a demonstration example. To illustrate the proposed method for robust design using coupled decisions, we present the simultaneous selection of gear material and gearbox geometry in a coupled decision environment while managing the uncertainties involved in designing gearboxes.

The unexpected effect of interruptions on garden-path problems

Interruptions are a regular part of daily life. As such, most people have many rules-of-thumbs they can use to deal with the consequences of such disruption. Here, we highlight a type of environment in which the typical approaches for dealing with interruptions could fail. We focus on "garden-path problems", where the features of a decision environment cause people to apply solutions that, while applicable in other situations, are presently inappropriate. Combining results from three experiments, we show that interruptions cause people to make more errors when solving such problems, while being unaware that the interruption affected their performance. We explain why this particular effect of interruptions is specific to garden-path problems, and is not simply because interruptions cause time pressure. Finally we suggest how people might adapt the ways in which they currently treat interruptions so as to minimize their detrimental effects on garden-path problems.