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Keywords = organizational neuroscience

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17 pages, 555 KiB  
Entry
The Emergence of Neuroleadership in the Knowledge Economy
by Constantin Bratianu and Roxana-Maria Staneiu
Encyclopedia 2024, 4(3), 1100-1116; https://doi.org/10.3390/encyclopedia4030071 - 1 Jul 2024
Viewed by 4246
Definition
“The Emergence of Neuroleadership in the Knowledge Economy” explores the field of neuroleadership in today’s constantly changing economy, highlighting the transition from traditional leadership to neuroleadership. Neuroleadership renders itself as a novel approach to the leadership theory, which brings together insights from neuroscience, [...] Read more.
“The Emergence of Neuroleadership in the Knowledge Economy” explores the field of neuroleadership in today’s constantly changing economy, highlighting the transition from traditional leadership to neuroleadership. Neuroleadership renders itself as a novel approach to the leadership theory, which brings together insights from neuroscience, psychology, and leadership studies. It emphasizes understanding the workings of the brain and human behavior in order to drive leadership effectiveness, at individual, team, and organizational levels. Additionally, the knowledge economy is characterized by the significant role of knowledge and intellectual capital when it comes to driving economic growth and organizational development. It highlights the creation, dissemination, and sharing of knowledge as important pillars for productivity and competitive advantage, shaping industries and transforming leadership traditional models. Through an extensive literature review and by employing the Dulewicz and Higgs leadership model, the authors showcase what are the intellectual, managerial, and emotional competencies that make neuroleadership the next natural step in leading teams and organizations. This article proposes a comparative matrix between traditional leaders and neuroleaders, and highlights a novel framework for better understanding neuroleadership. Full article
(This article belongs to the Collection Knowledge Management in Encyclopedia)
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3 pages, 140 KiB  
Abstract
The Development of a Research Scale for Neuroleadership
by Savaş Durmuş Bodur and Rana Özyurt Kaptanoğlu
Proceedings 2024, 101(1), 5; https://doi.org/10.3390/proceedings2024101005 - 2 May 2024
Viewed by 1413
Abstract
Neuroleadership is an up-to-date leadership approach that brings together the general findings of research on people’s brain structures and leadership, and as a result of this process, directs the leadership structure by revealing the facts behind people’s emotions, thoughts, and behaviors [...] Full article
15 pages, 563 KiB  
Communication
Human–Artificial Intelligence Systems: How Human Survival First Principles Influence Machine Learning World Models
by Stephen Fox
Systems 2022, 10(6), 260; https://doi.org/10.3390/systems10060260 - 17 Dec 2022
Cited by 4 | Viewed by 3056
Abstract
World models is a construct that is used to represent internal models of the world. It is an important construct for human-artificial intelligence systems, because both natural and artificial agents can have world models. The term, natural agents, encompasses individual people and human [...] Read more.
World models is a construct that is used to represent internal models of the world. It is an important construct for human-artificial intelligence systems, because both natural and artificial agents can have world models. The term, natural agents, encompasses individual people and human organizations. Many human organizations apply artificial agents that include machine learning. In this paper, it is explained how human survival first principles of interactions between energy and entropy influence organization’s world models, and hence their implementations of machine learning. First, the world models construct is related to human organizations. This is done in terms of the construct’s origins in psychology theory-building during the 1930s through its applications in systems science during the 1970s to its recent applications in computational neuroscience. Second, it is explained how human survival first principles of interactions between energy and entropy influence organizational world models. Third, a practical example is provided of how survival first principles lead to opposing organizational world models. Fourth, it is explained how opposing organizational world models can constrain applications of machine learning. Overall, the paper highlights the influence of interactions between energy and entropy on organizations’ applications of machine learning. In doing so, profound challenges are revealed for human-artificial intelligence systems. Full article
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14 pages, 1675 KiB  
Article
“We Will Let You Know”: An Assessment of Digital vs. Face-to-Face Job Interviews via EEG Connectivity Analysis
by Michela Balconi, Davide Crivelli and Federico Cassioli
Information 2022, 13(7), 312; https://doi.org/10.3390/info13070312 - 27 Jun 2022
Cited by 5 | Viewed by 3652
Abstract
We focused on job interviews as critical examples of complex social interaction in organizational contexts. We aimed at investigating the effect of face-to-face vs. computer-mediated interaction, of role (candidate, recruiter), and of the interview phase (introductory, attitudinal, technical, conclusive) on intra-brain and inter-brain [...] Read more.
We focused on job interviews as critical examples of complex social interaction in organizational contexts. We aimed at investigating the effect of face-to-face vs. computer-mediated interaction, of role (candidate, recruiter), and of the interview phase (introductory, attitudinal, technical, conclusive) on intra-brain and inter-brain connectivity measures and autonomic synchronization. Twenty expert recruiters and potential candidates took part in a hyperscanning investigation. Namely, electroencephalography (delta, theta, alpha, beta bands) and autonomic (skin-conductance, heart-rate) data were collected in candidate-recruiter dyads during a simulated job interview and then concurrently analyzed. Analyses highlighted a link between face-to-face condition and greater intra-/inter-brain connectivity indices in delta and theta bands. Furthermore, intra-brain and inter-brain connectivity measures were higher for delta and theta bands in the final interview phases compared to the first ones. Consistently, autonomic synchronization was higher during the final interview phases, specifically in the face-to-face condition. Finally, recruiters showed higher intra-brain connectivity in the delta range over frontal and temporoparietal areas, while candidates showed higher intra-brain connectivity in the theta range over frontal areas. Findings highlight the value of hyperscanning investigations in exploring social attunement in professional contexts and hint at their potential to foster neuroscience-informed practices in human resource management processes. Full article
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9 pages, 498 KiB  
Article
Using Machine Learning to Detect Theranostic Biomarkers Predicting Respiratory Treatment Response
by Vasilis Nikolaou, Sebastiano Massaro, Masoud Fakhimi and Wolfgang Garn
Life 2022, 12(6), 775; https://doi.org/10.3390/life12060775 - 24 May 2022
Cited by 2 | Viewed by 2340
Abstract
Background: Theranostic approaches—the use of diagnostics for developing targeted therapies—are gaining popularity in the field of precision medicine. They are predominately used in cancer research, whereas there is little evidence of their use in respiratory medicine. This study aims to detect theranostic biomarkers [...] Read more.
Background: Theranostic approaches—the use of diagnostics for developing targeted therapies—are gaining popularity in the field of precision medicine. They are predominately used in cancer research, whereas there is little evidence of their use in respiratory medicine. This study aims to detect theranostic biomarkers associated with respiratory-treatment responses. This will advance theory and practice on the use of biomarkers in the diagnosis of respiratory diseases and contribute to developing targeted treatments. Methods: We performed a cross-sectional analysis on a sample of 13,102 adults from the UK household longitudinal study ‘Understanding Society’. We used recursive feature selection to identify 16 biomarkers associated with respiratory treatment responses. We then implemented several machine learning algorithms using the identified biomarkers as well as age, sex, body mass index, and lung function to predict treatment response. Results: Our analysis shows that subjects with increased levels of alkaline phosphatase, glycated haemoglobin, high-density lipoprotein cholesterol, c-reactive protein, triglycerides, hemoglobin, and Clauss fibrinogen are more likely to receive respiratory treatments, adjusting for age, sex, body mass index, and lung function. Conclusions: These findings offer a valuable blueprint on why and how the use of biomarkers as diagnostic tools can prove beneficial in guiding treatment management in respiratory diseases. Full article
(This article belongs to the Special Issue Advances in Theranostic Biomarkers in Lung Diseases)
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16 pages, 1568 KiB  
Article
Organizational Neuroscience of Industrial Adaptive Behavior
by Stephen Fox and Adrian Kotelba
Behav. Sci. 2022, 12(5), 131; https://doi.org/10.3390/bs12050131 - 3 May 2022
Cited by 1 | Viewed by 2835
Abstract
Organizational neuroscience is recognized in organizational behavior literature as offering an interpretive framework that can shed new light on existing organizational challenges. In this paper, findings from neuroscience studies concerned with adaptive behavior for ecological fitness are applied to explore industrial adaptive behavior. [...] Read more.
Organizational neuroscience is recognized in organizational behavior literature as offering an interpretive framework that can shed new light on existing organizational challenges. In this paper, findings from neuroscience studies concerned with adaptive behavior for ecological fitness are applied to explore industrial adaptive behavior. This is important because many companies are not able to manage dynamics between adaptability and stability. The reported analysis relates business-to-business signaling in competitive environments to three levels of inference. In accordance with neuroscience studies concerned with adaptive behavior, trade-offs between complexity and accuracy in business-to-business signaling and inference are explained. In addition, signaling and inference are related to risks and ambiguities in competitive industrial markets. Overall, the paper provides a comprehensive analysis of industrial adaptive behavior in terms of relevant neuroscience constructs. In doing so, the paper makes a contribution to the field of organizational neuroscience, and to research concerned with industrial adaptive behavior. The reported analysis is relevant to organizational adaptive behavior that involves combining human intelligence and artificial intelligence. Full article
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19 pages, 2803 KiB  
Article
Combining Virtual Reality and Organizational Neuroscience for Leadership Assessment
by Elena Parra, Irene Alice Chicchi Giglioli, Jestine Philip, Lucia Amalia Carrasco-Ribelles, Javier Marín-Morales and Mariano Alcañiz Raya
Appl. Sci. 2021, 11(13), 5956; https://doi.org/10.3390/app11135956 - 26 Jun 2021
Cited by 9 | Viewed by 4080
Abstract
In this article, we introduce three-dimensional Serious Games (3DSGs) under an evidence-centered design (ECD) framework and use an organizational neuroscience-based eye-tracking measure to capture implicit behavioral signals associated with leadership skills. While ECD is a well-established framework used in the design and development [...] Read more.
In this article, we introduce three-dimensional Serious Games (3DSGs) under an evidence-centered design (ECD) framework and use an organizational neuroscience-based eye-tracking measure to capture implicit behavioral signals associated with leadership skills. While ECD is a well-established framework used in the design and development of assessments, it has rarely been utilized in organizational research. The study proposes a novel 3DSG combined with organizational neuroscience methods as a promising tool to assess and recognize leadership-related behavioral patterns that manifest during complex and realistic social situations. We offer a research protocol for assessing task- and relationship-oriented leadership skills that uses ECD, eye-tracking measures, and machine learning. Seamlessly embedding biological measures into 3DSGs enables objective assessment methods that are based on machine learning techniques to achieve high ecological validity. We conclude by describing a future research agenda for the combined use of 3DSGs and organizational neuroscience methods for leadership and human resources. Full article
(This article belongs to the Special Issue Applications of Virtual, Augmented, and Mixed Reality)
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12 pages, 1080 KiB  
Review
The Human Self Has Two Serial Aspects and Is Dynamic: A Concept Based on Neurophysiological Evidence Supporting a Multiple Aspects Self Theory (MAST)
by Peter Walla, Georg Northoff and Cornelia Herbert
Life 2021, 11(7), 611; https://doi.org/10.3390/life11070611 - 24 Jun 2021
Cited by 2 | Viewed by 3624
Abstract
The self is an increasingly central topic in current neuroscience. Understanding the neural processes that are involved in self-referential processing and functioning may also be crucial to understanding consciousness. The current short communication goes beyond the typical concept that the self is singular, [...] Read more.
The self is an increasingly central topic in current neuroscience. Understanding the neural processes that are involved in self-referential processing and functioning may also be crucial to understanding consciousness. The current short communication goes beyond the typical concept that the self is singular, as has been assumed from neuroanatomical descriptions of the self by fMRI and PET studies. Long ago, theoretically, the idea of multiple aspects of the human self-arose, highlighting a dynamic organizational structure, but an increasing number of electrophysiological brain imaging studies, searching for the temporal dynamics of self-referential brain processes, now has empirical evidence supporting their existence. This short communication focuses on the theoretical idea of a dynamic self and provides first preliminary empirical evidence, including results from own studies of the authors, in support of, and highlights the serial dynamics of the human self, suggesting a primitive Me1 and an elaborate Me2 (a non-personal and a personal self). By focusing on the temporal dimension of the self, we propose that multiple aspects of the self can be distinguished based on their temporal sequence. A multiple aspects Self Theory (MAST) is proposed. This model is meant as a theoretical framework for future studies providing further support. Full article
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16 pages, 602 KiB  
Review
Biomarker-Informed Machine Learning Model of Cognitive Fatigue from a Heart Rate Response Perspective
by Kar Fye Alvin Lee, Woon-Seng Gan and Georgios Christopoulos
Sensors 2021, 21(11), 3843; https://doi.org/10.3390/s21113843 - 2 Jun 2021
Cited by 19 | Viewed by 6500
Abstract
Cognitive fatigue is a psychological state characterised by feelings of tiredness and impaired cognitive functioning arising from high cognitive demands. This paper examines the recent research progress on the assessment of cognitive fatigue and provides informed recommendations for future research. Traditionally, cognitive fatigue [...] Read more.
Cognitive fatigue is a psychological state characterised by feelings of tiredness and impaired cognitive functioning arising from high cognitive demands. This paper examines the recent research progress on the assessment of cognitive fatigue and provides informed recommendations for future research. Traditionally, cognitive fatigue is introspectively assessed through self-report or objectively inferred from a decline in behavioural performance. However, more recently, researchers have attempted to explore the biological underpinnings of cognitive fatigue to understand and measure this phenomenon. In particular, there is evidence indicating that the imbalance between sympathetic and parasympathetic nervous activity appears to be a physiological correlate of cognitive fatigue. This imbalance has been indexed through various heart rate variability indices that have also been proposed as putative biomarkers of cognitive fatigue. Moreover, in contrast to traditional inferential methods, there is also a growing research interest in using data-driven approaches to assessing cognitive fatigue. The ubiquity of wearables with the capability to collect large amounts of physiological data appears to be a major facilitator in the growth of data-driven research in this area. Preliminary findings indicate that such large datasets can be used to accurately predict cognitive fatigue through various machine learning approaches. Overall, the potential of combining domain-specific knowledge gained from biomarker research with machine learning approaches should be further explored to build more robust predictive models of cognitive fatigue. Full article
(This article belongs to the Special Issue Brain Signals Acquisition and Processing)
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10 pages, 297 KiB  
Article
Prevalence of Vitamin D Deficiency and Its Associated Work-Related Factors among Indoor Workers in a Multi-Ethnic Southeast Asian Country
by Ushashree Divakar, Thirunavukkarasu Sathish, Michael Soljak, Ram Bajpai, Gerard Dunleavy, Nanthini Visvalingam, Nuraini Nazeha, Chee Kiong Soh, Georgios Christopoulos and Josip Car
Int. J. Environ. Res. Public Health 2020, 17(1), 164; https://doi.org/10.3390/ijerph17010164 - 25 Dec 2019
Cited by 23 | Viewed by 6716
Abstract
Little is known about the effect of working conditions on vitamin D status in Southeast Asia, where vitamin D deficiency is common despite the presence of sunlight all year round in most places. We examined the prevalence of vitamin D deficiency and its [...] Read more.
Little is known about the effect of working conditions on vitamin D status in Southeast Asia, where vitamin D deficiency is common despite the presence of sunlight all year round in most places. We examined the prevalence of vitamin D deficiency and its associated work-related factors among indoor workers using the data of 213 participants (aged ≥21 years) from a workplace cohort study in Singapore. Vitamin D deficiency was defined as serum 25-hydroxyvitamin D (25(OH)D) concentration <50 nmol/L. Data on work-related factors, socio-demographic characteristics, and lifestyle habits were collected using standardized questionnaires. Clinical and biochemical measurements were performed using standard tools and protocols. Multivariate Poisson regression was used to examine the independent association of work-related factors with vitamin D deficiency. Mean serum 25(OH)D concentration was 59.6 nmol/L. The prevalence of vitamin D deficiency was 32.9% (95% confidence interval (CI): 26.6–39.6%). In the multivariate analysis, office workers (prevalence ratio (PR): 2.16, 95% CI: 1.12–4.16 versus control room workers), workshop workers (PR: 2.25, 95% CI: 1.05–4.81 versus control room workers), and night shift workers (PR: 1.31, 95% CI: 1.03–1.67) were at a greater risk for vitamin D deficiency. Workplace policies and wellness programs should encourage workers to take regular breaks to go outdoors for sunlight exposure and to consume adequate amounts of vitamin D-rich foods to maintain optimal vitamin D levels. Full article
(This article belongs to the Special Issue Workplace Health and Wellbeing 2019)
11 pages, 487 KiB  
Article
Risk Factors for Non-Communicable Diseases at Baseline and Their Short-Term Changes in a Workplace Cohort in Singapore
by Thirunavukkarasu Sathish, Gerard Dunleavy, Michael Soljak, Nanthini Visvalingam, Nuraini Nazeha, Ushashree Divakar, Ram Bajpai, Thuan-Quoc Thach, Kei L Cheung, Hein de Vries, Chee-Kiong Soh, Georgios Christopoulos and Josip Car
Int. J. Environ. Res. Public Health 2019, 16(22), 4551; https://doi.org/10.3390/ijerph16224551 - 18 Nov 2019
Cited by 4 | Viewed by 5369
Abstract
We aimed to examine the behavioural and clinical risk factors for non-communicable diseases (NCDs) at baseline and their changes over 12 months in a workplace cohort in Singapore. A total of 464 full-time employees (age ≥ 21 years) were recruited from a variety [...] Read more.
We aimed to examine the behavioural and clinical risk factors for non-communicable diseases (NCDs) at baseline and their changes over 12 months in a workplace cohort in Singapore. A total of 464 full-time employees (age ≥ 21 years) were recruited from a variety of occupational settings, including offices, control rooms, and workshops. Of these, 424 (91.4%) were followed-up at three months and 334 (72.0%) were followed up at 12 months. Standardized questionnaires were used to collect data on health behaviours and clinical measurements were performed by trained staff using standard instruments and protocols. Age-adjusted changes in risk factors over time were examined using generalized estimating equations or linear mixed-effects models where appropriate. The mean age of the participants at baseline was 39.0 (SD: 11.4) years and 79.5% were men. Nearly a quarter (24.4%) were current smokers, slightly more than half (53.5%) were alcohol drinkers, two-thirds (66%) were consuming <5 servings of fruit and vegetables per day, and 23.1% were physically inactive. More than two-thirds (67%) were overweight or obese and 34.5% had central obesity. The mean follow-up was 8.6 months. After adjusting for age, over 12 months, there was a significant increase in the proportion consuming <5 servings of fruit and vegetables per day by 33% (p = 0.030), who were physically inactive by 64% (p < 0.001), and of overweight or obese people by 15% (p = 0.018). The burden of several key NCD risk factors at baseline was high and some worsened within a short period of time in this working population. There is a need for more targeted strategies for behaviour change towards a healthy lifestyle as part of the ongoing health and wellness programs at workplaces in Singapore. Full article
(This article belongs to the Special Issue Workplace Health and Wellbeing 2019)
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