Cognitive Decision Research Articles

Elites and ordinariness in cross-status encounters: Adding Goffman's ritual interaction order to sociological interpretations

Elites and higher-class people often downplay – even conceal – their status when interacting with people of lower class/status than themselves. This finding has been reported from several countries in the Global North. It is also shown in research from disparate academic fields and disciplines: the sociology of class, psychology, cognitive decision-making, and microsociology. This paper reviews and synthesises the literature on elites and high-status people who downplay social differences in cross-status social interaction. It makes two main contributions: First, I show that the phenomenon is more widespread transnationally than especially Nordic researchers have assumed. The second contribution comes from tracing the theoretical interpretations in the research. I notice tendencies of an individual – structure dualism in some strands of research, with the relevant analytical levels being the broader moral repertoires and predispositions. Other strands of research suffer from overly individualist interpretations. I argue that what is missing in most current research on cross-status interaction, is an adequate theoretical grasp of the social situation. I discuss how the study of cross-status interaction can be fertilised by the classical microsociological idea of situations’ existence in themselves, a social domain that cannot be reduced to dispositions or broader culture. I engage here especially Erving Goffman's ritual interaction order. From this vantage point, I also highlight situational variation, something attended to by few studies of cross-status interaction.

Different Effects of Attachment Anxiety and Avoidance on Attention to Changing Facial Expressions

AbstractAttachment orientation has been reported to influence visual attention and cognitive decisions regarding facial expressions. However, previous studies have reported mixed results regarding the effects of attachment orientation. This study aims to examine how attachment anxiety and avoidance affect judgment and attention allocation during free viewing of dynamic facial expressions. Although we did not find any association between attachment orientation and the reaction time to judge the timings of changes in facial expressions, the relationship between attachment orientation and attention was found. When viewing the appearance of anger, attachment avoidance had a positive relationship and attachment anxiety had a negative relationship with looking time to the eye area. When the eye‐tracking data were divided into 12 consecutive intervals of 1 s each, the attachment orientation had different relationships with visual attention based on the type of emotion presented. We discuss possible explanations for these results and directions for further research in cross‐cultural contexts.

Artificial olfactory memory system based on conductive metal-organic frameworks

The olfactory system can generate unique sensory memories of various odorous molecules, guiding emotional and cognitive decisions. However, most existing electronic noses remain constrained to momentary concentration, failing to trigger specific memories for different smells. Here, we report an artificial olfactory memory system utilizing conductive metal-organic frameworks (Ce-HHTP) that integrates sensing and memory and exhibits short- and long-term memory responses to alcohols and aldehydes. Experiments and theoretical calculations show that distinct memories are derived from the specific combinations of Ce-HHTP with O atoms in different guest. An unmanned aircraft equipped with this system realized the sensory memories in established areas. Moreover, the fusion of portable detection boxes and wearable flexible electrodes demonstrated the immense potential in off-site pollution monitoring and health management. This work represents an artificial olfactory memory system with two specific sensory memories under simultaneous conditions, laying the foundation for bionic design with qualities of human olfactory memory.

The Influence of AI-Driven Personalization on Consumer Decision-Making in E-Commerce Platforms

This research provides a comprehensive overview of the impact of AI-driven personalization on consumer decision-making in e-commerce platforms. It emphasizes the importance of understanding how AI impacts consumer behavior and the need to study its multifarious effects on various consumer groups, including Generation X and Millennials. The study aims to analyze the Consumer Decision-Making Model and the Cognitive Decision-Making Process, focusing on the pivotal decision-making phase where consumers choose to acquire a product or service influenced by external forces. It also highlights the disparities in consumer behavior and the innovative use of modern technology between these two generations, shedding light on their unique perspectives, behaviors, and attitudes towards AI-driven personalization, the research encapsulates the objectives, methodology, and key conclusions reached. It sets an awe-inspiring stage for a comprehensive exploration of the profound impact of AI-driven personalization on consumer decision-making within e-commerce, shaping the transformative trajectory of this rapidly growing industry. The expanded text effectively conveys the complexity of the subject matter with an intricate and thorough analysis, while maintaining coherence and succinctness throughout the expanded paragraph

A multiscale distributed neural computing model database (NCMD) for neuromorphic architecture

Distributed neuromorphic architecture is a promising technique for on-chip processing of multiple tasks. Deploying the constructed model in a distributed neuromorphic system, however, remains time-consuming and challenging due to considerations such as network topology, connection rules, and compatibility with multiple programming languages. We proposed a multiscale distributed neural computing model database (NCMD), which is a framework designed for ARM-based multi-core hardware. Various neural computing components, including ion channels, synapses, and neurons, are encompassed in NCMD. We demonstrated how NCMD constructs and deploys multi-compartmental detailed neuron models as well as spiking neural networks (SNNs) in BrainS, a distributed multi-ARM neuromorphic system. We demonstrated that the electrodiffusive Pinsky–Rinzel (edPR) model developed by NCMD is well-suited for BrainS. All dynamic properties, such as changes in membrane potential and ion concentrations, can be easily explored. In addition, SNNs constructed by NCMD can achieve an accuracy of 86.67% on the test set of the Iris dataset. The proposed NCMD offers an innovative approach to applying BrainS in neuroscience, cognitive decision-making, and artificial intelligence research.

Conceptualizing Automated Decision-Making in Organizational Contexts

Despite growing interest in automated (or algorithmic) decision-making (ADM), little work has been done to conceptually clarify the term. This article aims to tackle this issue by developing a conceptualization of ADM specifically tailored to organizational contexts. It has two main goals: (1) to meaningfully demarcate ADM from similar, yet distinct algorithm-supported practices; and (2) to draw internal distinctions such that different ADM types can be meaningfully distinguished. The proposed conceptualization builds on three arguments: First, ADM primarily refers to the automation of practical decisions (decisions to φ) as opposed to cognitive decisions (decisions that p). Second, rather than referring to algorithms as literally making decisions, ADM refers to the use of algorithms to solve decision problems at an organizational level. Third, since algorithmic tools by nature primarily settle cognitive decision problems, their classification as ADM depends on whether and to what extent an algorithmically generated output p has an action triggering effect—i.e., translates into a consequential action φ. The examination of precisely this p-φ relationship, allows us to pinpoint different ADM types (suggesting, offloading, superseding). Taking these three arguments into account, we arrive at the following definition: ADM refers to the practice of using algorithms to solve decision problems, where these algorithms can play a suggesting, offloading, or superseding role relative to humans, and decisions are defined as action triggering choices.

Cognitive Principles for Remote Condition Monitoring Applied to a Rail Pantograph System

Remote condition monitoring (RCM) aims to ensure the availability of railway assets. Previous work has indicated the importance of a user-centred RCM design approach based on cognitive principles, but there has been no known demonstration of the application of these principles. The following paper takes this theory-based approach and applies it to the design of an RCM system for the rail pantograph/Overhead Line (OHL) system. The paper first presents a high-level conceptual architecture, based on four stages of cognitive decision-making (notification, acceptance, analysis and clearance), linked to the wider monitoring architecture. Second, the paper uses cognitive principles to propose demonstration Human–Machine Interface designs for the OHL system. These HMIs were presented in an evaluation with subject matter experts. The outcomes of the process generated user-centred design recommendations for RCM. Furthermore, the evaluation suggested the importance of multiple paths through the HMI dependent on the type and urgency of fault. Finally, the outcomes of the evaluation also highlighted the importance of considering context when deploying user-centred RCM.

Analyzing the Effects of Cognitive Decision Training on Decision-Making Skills in sports – A Theoretical Assimilation

Analyzing the Effects of Cognitive Decision Training on Decision-Making Skills in sports – A Theoretical Assimilation

Sports Participants' Intentions to Use Digital Technology for Sports Participation: A Behavioral Reasoning Theory Perspective

The use of digital technology in sport is an inevitable trend, but the behavioral decision-making process of sport participants using digital technology for sport participation is unclear. This study used behavioral reasoning theory to develop and validate a theoretical model that analyses participants’ behavioral cognitive decision-making by considering both reasons for adoption and against adoption and in doing so, explains sport participants’ behavioral decision-making in using digital technology for sport participation, which is a theoretical extension of existing innovation frameworks in sport management and marketing. The study found that respondents’ reasons against adoption the use of digital technology for sport participation had a greater influence on their attitudes and behavioral intentions, with perceived hedonism and barriers to use being the dominant factors in the reason for adoption and against adoption, respectively, and participants’ values significantly influencing the reasons for adoption and against adoption the use of digital technology for sport participation. This study provides unique insights for developers and related marketing promoters of digital technology applications in sport, and in expanding the impacts associated with the use of digital technology in sport, it is necessary to clarify the reasons for adoption and against adoption, and to consider the values of the participants, so that the combination of digital technology and sport can better meet the actual needs of the participants.

Conflicting cognitive decisions: Does egg retrieval modify egg rejection in a host of an obligate brood parasite?

AbstractEgg retrieval is an ancient behaviour displayed by birds in which a displaced egg is transferred back into the nest. Egg rejection, in contrast, is a recently evolved adaptation by hosts of brood parasites in which an egg is removed from a nest. These conflicting behaviours are both adaptive because they prevent reproductive losses, but egg retrieval may benefit brood parasites if hosts retrieve parasitic eggs into their nests. We examined these conflicting cognitive processes in the prothonotary warbler (Protonotaria citrea), a cavity‐nesting host of the brown‐headed cowbird (Molothrus ater). Eggs and nestlings are occasionally found on the rims of warbler nest cavities. We determined how this happened using video cameras and tested whether warblers retrieved their own eggs more often than cowbird eggs. We also determined if shape affects retrieval and rejection by placing cylinders inside nest cups or onto nest rims. We found that eggs were displaced by rapidly departing warblers whose nests are constantly prospected by nest competitors and brood parasites. Warblers retrieved their eggs (29%) and cowbird eggs (19%) at similar rates, and never rejected cowbird eggs after retrieval. Warblers removed most cylinders from nest rims and cups (89% and 78%, respectively), and never retrieved them. Warblers have retained egg retrieval at a low level and its expression is costly because they only retrieve a low level of their own eggs and also retrieve cowbird eggs, which benefits the brood parasite.

Building a successful robotic-arm assisted orthopedic surgery program

Building a successful robotics team is a long journey with much effort before the first surgery. It starts with sound business development and, in case of acquiring a system, an implementation plan, to make it a success. The pathway to a successful Robotics program is much more than choosing the desired robotic arm-assisted surgery (RAS) brand. Success also depends on the specific pathway optimization aspects of RAS. High-over, all systems introduce the computer and robotic-arm into the operating room. But all systems have subtle, but significant, differences. An essential aspect of a successful RAS project is the implementation phase. After deciding to purchase a Robotic system, the following training and OR setup phase should be prepared and executed. When the robotic system enters the operating room, aspects like arm position using the arm board should be evaluated critically since the robot needs sufficient working space. A suboptimal positioning will disrupt the team dynamics and lead to preventable delay. RAS requires new or adjusted skills. Two crucial aspects are eye-hand-feet coordination in combination with a different focus of the surgeon (also screen instead of 100% surgery field) and new cognitive decision making features. Robotic surgery is a perfect example of how technology can change a surgical field. This data acquisition is probably the most fundamental, powerful aspect of adding the computer into the surgical process. The most used robotic-arm systems in hip and knee arthroplasty are semi-automatic systems, and practically all major orthopedic manufacturers offer a device. ORs are a highly capitalized section of hospitals, generating high costs and critical revenues. Therefore, taking a closer look at workflows, inventory management, and team efficiencies is crucial. Improving these aspects in the OR has a high return on investment. RAS helps accurately observe everything occurring within and around the surgical process. These new data opportunities open the opportunity to work with surgical data science (SDS).

Dissecting Bayes: Using influence measures to test normative use of probability density information derived from a sample.

Bayesian decision theory (BDT) is frequently used to model normative performance in perceptual, motor, and cognitive decision tasks where the possible outcomes of actions are associated with rewards or penalties. The resulting normative models specify how decision makers should encode and combine information about uncertainty and value-step by step-in order to maximize their expected reward. When prior, likelihood, and posterior are probabilities, the Bayesian computation requires only simple arithmetic operations: addition, etc. We focus on visual cognitive tasks where Bayesian computations are carried out not on probabilities but on (1) probability density functions and (2) these probability density functions are derived from samples. We break the BDT model into a series of computations and test human ability to carry out each of these computations in isolation. We test three necessary properties of normative use of pdf information derived from a sample-accuracy, additivity and influence. Influence measures allow us to assess how much weight each point in the sample is assigned in making decisions and allow us to compare normative use (weighting) of samples to actual, point by point. We find that human decision makers violate accuracy and additivity systematically but that the cost of failure in accuracy or additivity would be minor in common decision tasks. However, a comparison of measured influence for each sample point with normative influence measures demonstrates that the individual's use of sample information is markedly different from the predictions of BDT. We will show that the normative BDT model takes into account the geometric symmetries of the pdf while the human decision maker does not. An alternative model basing decisions on a single extreme sample point provided a better account for participants' data than the normative BDT model.

Frequency dependence of human thresholds: both perceptual and vestibuloocular reflex thresholds.

Although perceptual thresholds have been widely studied, vestibuloocular reflex (VOR) thresholds have received less attention, so the relationship between VOR and perceptual thresholds remains unclear. We compared the frequency dependence of human VOR thresholds to human perceptual thresholds for yaw head rotation in both upright ("yaw rotation") and supine ("yaw tilt") positions, using the same human subjects and motion device. VOR thresholds were generally a little smaller than perceptual thresholds. We also found that horizontal VOR thresholds for both yaw rotation about an Earth-vertical axis and yaw tilt (yaw rotation about an Earth-horizontal axis) were relatively constant across four frequencies (0.2, 0.5, 1, and 2 Hz), with little difference between yaw rotation and yaw tilt VOR thresholds. For yaw tilt stimuli, perceptual thresholds were slightly lower at the lowest frequency and nearly constant at all other (higher) frequencies. However, for yaw rotation, perceptual thresholds increased significantly at the lowest frequency (0.2 Hz). We conclude 1) that VOR thresholds were relatively constant across frequency for both yaw rotation and yaw tilt, 2) that the known contributions of velocity storage to the VOR likely yielded these VOR thresholds that were similar for yaw rotation and yaw tilt for all frequencies tested, and 3) that the integration of otolith and horizontal canal signals during yaw tilt when supine contributes to stable perceptual thresholds, especially relative to the low-frequency perceptual thresholds recorded during yaw rotation.NEW & NOTEWORTHY We describe for the first time that human VOR thresholds differ from human forced-choice perceptual thresholds, with the difference especially evident at frequencies below 0.5 Hz. We also report that VOR thresholds are relatively constant across frequency for both yaw rotation and yaw tilt. These findings are consistent with the idea that high-pass filtering in cortical pathways impacts cognitive decision-making.

Urban Landscape Perception Research Based on the ERP Method: A Case Study of Jingdezhen, China

Within the rapidly growing urban tourism industry, the development of urban landscapes plays a crucial role in shaping a city’s image and competitiveness; however, standardized and mismatched landscapes often have a negative impact, highlighting the importance of assessing urban landscape perceptions. Although existing studies have discussed this through subjective questionnaires and physiological methods, the underlying neural mechanisms have not been thoroughly explored. The research focuses on Jingdezhen, a renowned historical and cultural city in China, as its case study. Utilized the event-related potential (ERP) method to explore individuals’ perceptual consistency and neural activity toward different types of urban landscapes. We adopted a 2 (landscape type: historical, modern) X 2 (perceptual match: consistent, inconsistent) within-subject design while recording behavioral data and electrophysiological responses. The results showed that, under any condition, there were no significant differences in people’s behavioral data. Neurophysiological results indicate that consistent perceptions of modern landscapes elicited greater P200 responses, suggesting increased attention driven by visual aesthetics and emotional activation. Under conditions of perceptual inconsistency, historical landscapes elicited higher N400 amplitudes than modern landscapes, revealing cognitive conflict and effort. This study demonstrates that P200 and N400 components are effective indicators for assessing urban perception, proving the viability of the event-related potential method in urban landscape research. Additionally, the research reveals the neural mechanisms of urban environmental perception from the early stages of attention and emotional distribution to the later stages of cognitive decision-making, which involve cognitive processes from “bottom-up” to “top-down”. This study not only provides a reference for efficient design planning for those involved in urban science but also inspires the coordination between the developmental needs of historical and modern urban landscapes. Moreover, it offers a new perspective for an interdisciplinary approach to urban perception assessment.

Multidisciplinary teams and social science: a patient perspective.

Multidisciplinary teams (MDTs) are common in colorectal cancer and have been deemed important when providing care. Yet they take place outside of the patient, often with little consideration of the patient's views, goals and desires. In this paper specific examples from a patient perspective are integrated with the social science literature to provide an overview of areas of disconnect between MDT recommendations and the individual patient. The reasons for these disconnects are explored, including how MDTs relate to dyadic patient-clinician relationships, weak incorporation of patient-oriented outcomes in MDTs, poor integration of nonmedical patient information and the patient perspective and the impact of team dynamics and cognitive decision biases. Consideration of these issues should facilitate higher-quality MDT recommendations that are also more acceptable to patients.

Optimized Attention Enhanced Temporal Graph Convolutional Network Espoused Research of Intelligent Customer Service System based on Natural Language Processing Technology

ABSTRACT Consumers have begun to move their attention away from product functioning and toward value probably extracted from items. Companies have begun to use customer service systems (CSS) in response to this trend, which are business models that give clients with not solitary tangible items as well as intangible facilities. Even with substantial investigation on Smart CSS frameworks, rare of this frameworks considered customers active data producers actively creating data for the Smart CSS. Furthermore, the majority of them offered a generic remedy rather than a personalized one. To classify customer service systems, performance metrics, such as precision, accuracy, F1-score, Recall (Sensitivity), Specificity, Error rate, Computation time, and RoC are considered. The performance of AETGCN-NGOA-CSS approach attains 19.11%, 24.12% and 28.13% high specificity, 24.93%, 23.04%, and 9.51% lower computation time, 15.2%, 25.45% and 13.91% higher ROC and 8.45%, 20.98%, and 27.55% higher accuracy compared with existing methods, such as developing personalized recommendation system in smart product service system depend on unsupervised learning model (CSS-BERT), Cognitive Decision-Making approaches in Data-driven Retail Intelligence: Consumer Sentiments, Choices, Shopping Behaviors (CSS-CDMA), e-Commerce Online Intelligent Customer Service System under Fuzzy Control (CSS-FFNN), respectively.

Impact of stakeholder engagement strategies on managerial cognitive decision-making: the context of CSP and CSR

PurposeThis study aims to explore the strategies corporations use in engaging stakeholders to sustain healthy corporate partnerships and create value for the corporate entity and the society in which they operate and their influence on the corporate manager’s cognitive abilities and decision-making.Design/methodology/approachThe authors used an interpretive research approach leveraging the strengths of qualitative method of content analysis and comparative and critical analyses to report the results. Interpretive methods incorporate social theories and standpoints that view reality as the social construction of understandable events in the context of organizational communication.FindingsThe findings of this study suggest that corporations are assumed to follow and execute the principles of engaging stakeholders to achieve corporate social responsibility (CSR) claiming to manage a sustainable and responsible business practices that recognize local cultures, human rights and protect the environment. However, little attention has been paid to the cognitive reasoning of the individuals responsible for CSR and corporate sustainability (CS) as opposed to the growing concerns about strategies corporations use in engaging stakeholders to sustain healthy corporate partnerships and create value – especially the processes that take place during engagement and decision-making including cognitive offloading.Practical implicationsStakeholder engagement requires practical approaches that enable corporations and individuals charged with decision-making responsibilities to understand, respond and fulfill their CSRs. To achieve CSRs, corporations and managers responsible for relevant decision-making would need to involve stakeholders in social performance planning, as social reporting/auditing has long been advocating for preventing managerial biasness, groupthink and increased information dissemination via detailed reporting practices toward more collaborative stakeholder relationships. Thus, it is crucial for corporations to implement enhanced stakeholder and managerial decision-making strategies such as integrative approaches to achieve balance in the trio elements of sustainability as well as the growing use of paradox perspective to understand the nature of the tensions being sought to balance and, in the process, provide opportunity for a better evaluation of complex sustainability issues for innovative approach to resolving them. While cognitive decision-making is at play, in practice, managers tasked with making decisions must ensure the most effective stakeholder engagement strategies that are transparent and inclusive are used.Originality/valueThe main contribution of this study is its argument regarding the tools corporations use in engaging key stakeholders and the cognitive reasoning of the individuals responsible for CSR and CS. The study further contributes to interpreting the integrative approach to achieving balance in the trio elements of sustainability as well as the growing use of paradox perspective to understand the nature of the tensions being sought to balance and, in the process, provide an opportunity for a better evaluation of complex sustainability issues for an innovative approach to resolving them.

Shared decision-making and social science: A patient perspective.

Shared decision making (SDM) between doctors and patients has been deemed important when providing care. Yet, it can be difficult to achieve. Specific examples from a patient perspective are integrated with the social science literature to provide an overview of components of SDM including the role of fit, trust, information asymmetry, cognitive decision frames and balancing medical and patient outcomes. Consideration of these issues should facilitate higher quality SDM conversations.

Deciphering Decision Making: The Interplay of Mood States and Decision Styles

Recent theories of Decision- Making have advocated the role of emotions in the cognitive processes of decisions. One such approach is the EIC model (Lerner et al., 2015) which posits – mood to indirectly affect decision making by impacting current emotions, indicating individual’s overall emotional states to indirectly influence cognitive decision processes. The study aimed to understand the role of emotions on decision making and the nuances that underlie it. The 6 main hypothesis of the paper focused on evaluating whether incidental emotions via current emotions affect decision making significantly or do decision styles have a stronger significant effect on decision making. The paper used a mixed method design where the qualitative data was collected via interviews and thematic analysis and labels were attuned via open coding that helped in triangulation and pattern generation. Tools used were the YDMC, Mood induction videos of OPENLAV Database, Decision Style questionnaire (DSQ), Ryff’s well-being scale and an Interview schedule. A purposive sampling was done to obtain the sample (N=29) for the pre-test post-test design. Results for the quantitative data concluded that sad and angry incidental mood had significant effects on FR1 and FR2 (Resistance to Framing and Sunken costs) of YDMC and, that happy mood had no significant effect on risk perception. The decision styles that have been seen to dominate were Vigilant followed by Dependent and Spontaneous style. For qualitative data, based on the dominant responses for the entire sample an Interactive Hexagonal map was constructed. STB (Self -thoughts & Beliefs), FP (Futuristic perspective), CE (Current experiences), EE (Environmental ‌effects), and PEx (Past experiences) were the dominant pattern connections found for the current sample. Thus, Incidental Mood had a significant effect on Resistance to Framing and Sunken costs whereas had no significant effect on Consistency with Risk Perception. Future work on the nuances of mood on decision-making can help determine the affective, cognitive, and neuropsychological models of decision-making where neural correlates could help delve deeper in these higher cognitive and emotional processes.

Polyvictimization and Impairments in Functioning for Children and Youth with Fetal Alcohol Spectrum Disorder

ABSTRACT Introduction Children with fetal alcohol spectrum disorder (FASD), a neurodevelopmental disorder associated with cognitive, emotional, and learning impairments have an increased likelihood of experiencing behavioral and socio-emotional difficulties and historical trauma. Methods Using the interRAI Child and Youth Mental Health instrument, this study examined associations between FASD, polyvictimization, daily cognitive decision-making, family functioning, and externalizing problems in 18,701 children and youth from 4 to 18 years of age (M age = 12.33, SD age = 3.53). Results Children with FASD, compared to children without FASD, were at an increased risk of being polyvictimized, were more likely to endorse greater difficulties with daily cognitive decision-making and family dysfunction, and scored higher on proactive and reactive aggression. Conclusion The findings highlight the increased risk of individual and familial difficulties in children diagnosed with FASD. The limitations and clinical implications are discussed to inform further research and assist in the development of trauma-informed clinical interventions.