Behavioral Decision Making in Normative and Descriptive Views: A Critical Review of Literature

Recent studies on decision analytics frequently refer to the topic of behavioral decision making (BDM), which focuses on behavioral components of decision analytics. This paper provides a critical review of literature for re-examining the relations between BDM and classical decision theories in both normative and descriptive reviews. We attempt to capture several milestones in theoretical models, elaborate on how the normative and descriptive theories blend into each other, thus motivating the mostly prescriptive models in decision analytics and eventually promoting the theoretical progress of BDM—an emerging and interdisciplinary field. We pay particular attention to the decision under uncertainty, including ambiguity aversion and models. Finally, we discuss the research directions for future studies by underpinning the theoretical linkages of BDM with fast-evolving research areas, including loss aversion, reference dependence, inequality aversion, and models of quasi-maximization mistakes. This paper helps to understand various behavioral biases and psychological factors when making decisions, for example, investment decisions. We expect that the results of this research can inspire studies on BDM and provide proposals for mechanisms for the development of D-TEA (decision—theory, experiments, and applications).

Behavioral data assists decisions: exploring the mental representation of digital-self

Purpose The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell. Design/methodology/approach In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making. Findings The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest. Originality/value In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

084 Does Alignment between the Timing of Sleep and Circadian Rhythm Predict Behavioral Decision Making?

Introduction Cognitive performance and decision making have been shown to suffer under conditions of misalignment between circadian preference and time-of-assessment; however, little is known about how misalignment between the timing of sleep and circadian rhythm impacts decision making. To this end, this study captured naturally occurring degrees of alignment between the timing of sleep and the circadian rhythm (i.e., alignment of sleep-wake timing with circadian phase) to examine if greater misalignment predicts worse behavioral decision making. Methods Over the course of two weeks, 32 participants (18–22 years of age; 61% female; 69% White) continuously wore actigraphs and completed two overnight in-lab visits (Thursday and Sunday) in which both dim light melatonin onset (DLMO) and behavioral decision-making (risk taking, framing, and strategic reasoning tasks) were assessed. Sleep-wake timing was assessed by actigraphic midsleep from the two nights prior to each in-lab visit. Alignment was operationalized as the interval between DLMO and average midsleep. Multilevel modeling was used to predict performance on decision making tasks from circadian alignment during each in-lab visit; nonlinear associations were also examined. Results Misalignment characterized by shorter time between DLMO and midsleep predicted decision-making in a curvilinear fashion (i.e., squared misalignment term predicted performance). Specifically, shorter time between DLMO and midsleep predicted greater risk-taking under conditions of potential loss (B = .10, p = .04), but less risk-taking under conditions of potential reward (B = -.14, p = .04) in a curvilinear fashion. Misalignment did not predict decision-making in the framing and strategic reasoning tasks. Conclusion Findings suggest that naturally occurring degrees of misalignment between the timing of sleep and the circadian rhythm may impact risky decision-making, further extending accumulating evidence that sleep/circadian factors are tied to risk-taking preferences. Future studies will need to replicate findings and experimentally probe whether manipulating alignment influences risky decision making. Support (if any) R21AA023209; R01DA044143

A tomada de decisão sob a perspectiva cognitiva

Esta pesquisa teve como objetivo investigar as estratégias de pesquisa utilizadas em estudos sobre tomada de decisão comportamental e cognição. Para tanto, procedeu-se um estudo bibliométrico com 2.001 artigos, disponibilizados na plataforma de pesquisa Web of Science, no período de 2009 a 2019, ao pesquisar os termos Behavioral decision making or Cognition nas categorias Business e Management. A partir dos estudos detectados, optou-se por avaliar detalhadamente os 13 estudos que se associaram às temáticas de tomada de decisão comportamental e cognição, bem como estavam incluídos nos parâmetros do índice h obtido. Os resultados permitiram apresentar uma visão ampla da produção acadêmica sobre o tema, bem como as estratégias de pesquisa utilizadas. Em geral, os estudos sobre decisão e cognição são de natureza qualitativa, do tipo descritivo, com delineamento teórico, a fonte de evidências sendo a análise documental e, não apresentam análise específica.