Decision Research

Multi-attribute decision-making (MADM) is a critical area of research in decision theory, often utilized for evaluating and selecting alternatives in complex scenarios. This paper introduces an innovative decision-making approach by combining the Picture Fuzzy Einstein Operator (PFE) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Picture fuzzy sets offer a rich representation of uncertainty and vagueness, which is essential for real-world decision problems. The Einstein operation serves as a flexible aggregation method for combining information from multiple sources. By incorporating the TOPSIS method, which ranks alternatives based on their distance from an ideal solution, we aim to enhance the accuracy and robustness of decision-making. The paper applies the proposed method to a practical example to demonstrate its efficacy and compares it with traditional fuzzy set-based approaches.

Laughing is ubiquitous in human life, yet what causes it and how it sounds is highly variable. Considering this diversity, we sought to test whether there are fundamentally different kinds of laughter. Here, we sampled spontaneous laughs (n = 887) from a wide range of everyday situations (e.g. comedic performances and playful pranks). Machine learning analyses showed that laughs produced during tickling are acoustically distinct from laughs triggered by other kinds of events (verbal jokes, watching something funny or witnessing someone else's misfortune). In a listening experiment (n = 201), participants could accurately identify tickling-induced laughter, validating that such laughter is not only acoustically but also perceptually distinct. A second listening study (n = 210) combined with acoustic analyses indicates that tickling-induced laughter involves less vocal control than laughter produced in other contexts. Together, our results reveal a unique acoustic and perceptual profile of laughter induced by tickling, an evolutionarily ancient play behaviour, distinguishing it clearly from laughter caused by other triggers. This study showcases the power of machine learning in uncovering patterns within complex behavioural phenomena, providing a window into the evolutionary significance of ticking-induced laughter.

In this commentary we expand on the special issue themes of applied affective science, ecologically valid data and application, and the need for transdisciplinary collaboration by discussing and exemplifying how affective science can inform behavioral public policy.

Off-label repurposing of empagliflozin allows pathomechanism-based treatment of neutropenia/neutrophil-dysfunction in glycogen storage disease type Ib (GSDIb). From a value-based healthcare (VBHC) perspective, we here retrospectively studied patient-reported, clinical and pharmacoeconomic outcomes in 11 GSDIb individuals before and under empagliflozin at two centers (the Netherlands [NL], Austria [AT]), including a budget impact analysis, sensitivity-analysis, and systematic benefit-risk assessment. Under empagliflozin, all GSDIb individuals reported improved quality-of-life-scores. Neutrophil dysfunction related symptoms allowed either granulocyte colony-stimulating factor cessation or tapering. Calculated cost savings per patient per year ranged between € 6482-14 190 (NL) and € 1281-41 231 (AT). The budget impact analysis estimated annual total cost savings ranging between € 75 062-225 716 (NL) and € 37 697-231 790 (AT), based on conservative assumptions. The systematic benefit-risk assessment was favorable. From a VBHC perspective, empagliflozin treatment in GSDIb improved personal and clinical outcomes while saving costs, thereby creating value at multiple pillars. We emphasize the importance to reimburse empagliflozin for GSDIb individuals, further supported by the favorable systematic benefit-risk assessment. These observations in similar directions in two countries/health care systems strongly suggest that our findings can be extrapolated to other geographical areas and health care systems.

This paper reviews the developmental literature on decision making, discussing how increased reliance on gist thinking explains the surprising finding that important cognitive biases increase from childhood to adulthood. This developmental trend can be induced experimentally by encouraging verbatim (younger) versus gist (older) ways of thinking. We then build on this developmental literature to assess the developmental stage of artificial intelligence (AI) and how its decision making compares with humans, finding that popular models are not only irrational but they sometimes resemble immature adolescents. To protect public safety and avoid risk, we propose that AI models build on policy frameworks already established to regulate other immature decision makers such as adolescents.

Financial behavior is intended to understand the behavior of investors in making investment decisions. Decision-making is a process to select the best alternative from available possible alternatives in a complex situation. Decision-making in investments is influenced by knowledge of fundamental analysis, technical analysis, and investor psychology in the capital market. This study aims to determine the behavior of investors in decision-making in investments in the capital market. There were eight informants interviewed in this study from various backgrounds, including brokers, university students, private employees, and investment managers. The result of this study showed the behavior of investors in decision-making in investments in . In making a decision, investors paid less attention to intrinsic value of stocks when stocks are in an uptrend condition and were overconfident in making decisions. Meanwhile, stock investor decisions were quite influenced by fundamental conditions, macroeconomics, and technical stock price fluctuation, so the behavior of individual stock investors in decision-making in tends to be rational.

Scholars, decision-makers, and pundits have long tossed around words and numbers meant to demarcate those health/safety risks that are too small to matter at all (called, variously, “trivial” or “de minimis” or “insignificant”), or risks that are so large as to be abhorrent (“unacceptable,” “intolerable,” and the like). But there has been nothing approaching a consensus about how large or small these important probabilities are, and worse, there have been no serious attempts to explore these concepts via any carefully-elicited preferences from laypeople themselves. Perhaps even more concerning, the dominant paradigm—cost-benefit analysis (CBA)—requires balancing of (monetized) risks against the costs of controlling them, but the parallel concepts of de minimis costs and intolerable costs have never been formally considered. As a result of these lapses, all attempts to consider equity or justice in the distribution of how risks and costs are borne are an absurdity, despite claims to the contrary. This article reports on a pair of elicitations involving 1350 laypeople. In one elicitation, a careful set of background and contextual explanations and a structured series of questions probed where each subject perceived lifetime excess mortality risk (from involuntary exposure) to become “so small you would not spend a moment thinking about it,” and where it becomes so large that “you would strongly object, as an ethical matter, to ever having to face it.” With a separate sample, we asked the parallel questions with regard to regulatory costs imposed by the government in the name of risk reduction. Although there was significant interindividual variation in responses, the central tendency of each of these four science-policy-values “goalposts” was as follows: (1) de minimis risk—a lifetime excess chance of premature death of 1 in 770,000; (2) intolerable risk—1 chance in 570; (3) de minimis cost—$25 per year; and (4) intolerable cost—$775 per year. These results offer, for the first time, a principled and evidence-based starting point for further refinement of which risks or costs to individuals can/should be disregarded in setting policy, and which must dominate policies regardless of how total “monetized lives saved” and total dollar costs compare to each other when viewed simplistically. We offer several prescriptions for how CBA might change, and how environmental/health/safety policy might improve, to take account of these fundamental thresholds in how risks and costs actually impose burdens on citizens. Both those interventions that impose intolerable costs while only reducing diffuse and trivially small risks, and those failures to intervene (sufficiently) that perpetuate intolerable risks for the sake of avoiding trivial and eminently manageable costs, are inefficient, unjust, and are thus unethical.