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The Role of Neurotechnology in Shaping Business Decisions: A Comprehensive Literature Review
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This study aimed to determine the content of 23 bioelements in the hair of 110 adolescents aged 13-17 years in Ulaanbaatar, the capital of Mongolia. The bioelements were categorized into macroelements (MaE), microelements (MiE), and ultramicroelements (UMiE). Participants, including birth parents, guardians, and teachers of Mongolian high schools from 2000 to 2003, were involved with consent from the school administration. A total of 111 individuals were enrolled in the study, with 110 providing hair samples. Hair analysis was employed as a convenient, non-invasive, and painless method to evaluate the concentrations of bioelements and toxic metals in adolescents. Micronutrients were classified as essential or toxic. Statistical analysis was conducted using mean values, t-tests, standard deviations, and comparative methods.
Operational environments are characterized by a range of psycho-physiological constraints that can degrade combatants’ performance and impact on their long-term health. Neurofeedback training (NFT), a non-invasive, safe and effective means of regulating brain activity, has been shown to be effective for mental disorders, as well as for cognitive and motor capacities and aiding sports performance in healthy individuals. Its value in helping soldiers in operational condition or suffering from post-traumatic stress (PTSD) is undeniable, but relatively unexplored. The aim of this narrative review is to show the applicability of NFT to enhance cognitive performance and to treat (or manage) PTSD symptoms in the military context. It provides an overview of NFT use cases before, during or after military operations, and in the treatment of soldiers suffering from PTSD. The position of NFT within the broad spectrum of performance enhancement techniques, as well as several key factors influencing the effectiveness of NFT are discussed. Finally, suggestions for the use of NFT in the military context (pre-training environments, and during and post-deployments to combat zones or field operations), future research directions, recommendations and caveats (e.g., on transfer to operational situations, inter-individual variability in responsiveness) are offered. This review is thus expected to draw clear perspectives for both researchers and armed forces regarding NFT for cognitive performance enhancement and PTSD treatment related to the military context.
The integration of big data analytics in digital marketing has fundamentally transformed how organizations understand and influence consumer behavior. This systematic review explores the potential of big data to offer deep insights into consumer preferences and behaviors. The current literature on big data and consumer behavior showcases its potential in enhancing marketing and customer experiences. However, significant gaps exist, such as longitudinal studies on how continuous big data–driven personalization affects consumer trust and loyalty over time. Addressing these gaps will advance academic understanding and offer practical insights for optimizing marketing strategies and improving customer experiences ethically. Focusing on these areas will contribute to a holistic view of big data’s responsible use in digital marketing. By utilizing large datasets, businesses can now tailor their marketing strategies to individual consumers, enhancing customer satisfaction and engagement. Adopting the PRISMA methodology, this review synthesizes recent literature to evaluate the benefits of big data in digital marketing. The research was conducted through a rigorous five-stage process, encompassing the identification of key research questions, database searches, and the critical analysis of selected articles: (1) defining the initial topic, (2) developing the appropriate research questions, (3) identifying the necessary keywords, (4) identifying and searching databases, and finally (5) accessing and reading the articles. The databases that were searched were as follows: Scopus, Web of Science, Emerald Insight, Springer Link, and ScienceDirect. The articles that were selected were 19, in a total sum of 265 identified articles. The findings consolidate current knowledge on how big data analytics can optimize marketing strategies and consumer experiences. Ultimately, this review underscores the transformative potential of big data in digital marketing, highlighting its role in enhancing customer insights and driving more effective marketing strategies.
Computer-based learning has gained popularity in recent years, providing learners greater flexibility and freedom. However, these learning environments do not consider the learner’s mental state in real-time, resulting in less optimized learning experiences. This research aimed to explore the effect on the learning experience of a novel EEG-based Brain-Computer Interface (BCI) that adjusts the speed of information presentation in real-time during a learning task according to the learner’s cognitive load. We also explored how motivation moderated these effects. In accordance with three experimental groups (non-adaptive, adaptive, and adaptive with motivation), participants performed a calibration task (n-back), followed by a memory-based learning task concerning astrological constellations. Learning gains were assessed based on performance on the learning task. Self-perceived mental workload, cognitive absorption and satisfaction were assessed using a post-test questionnaire. Between-group analyses using Mann–Whitney tests suggested that combining BCI and motivational factors led to more significant learning gains and an improved learning experience. No significant difference existed between the BCI without motivational factor and regular non-adaptive interface for overall learning gains, self-perceived mental workload, and cognitive absorption. However, participants who undertook the experiment with an imposed learning pace reported higher overall satisfaction with their learning experience and a higher level of temporal stress. Our findings suggest BCI’s potential applicability and feasibility in improving memorization-based learning experiences. Further work should seek to optimize the BCI adaptive index and explore generalizability to other learning contexts.
This study explores neuroplasticity through the use of virtual reality (VR) and brain–computer interfaces (BCIs). Neuroplasticity is the brain’s ability to reorganize itself by forming new neural connections in response to learning, experience, and injury. VR offers a controlled environment to manipulate sensory inputs, while BCIs facilitate real-time monitoring and modulation of neural activity. By combining VR and BCI, researchers can stimulate specific brain regions, trigger neurochemical changes, and influence cognitive functions such as memory, perception, and motor skills. Key findings indicate that VR and BCI interventions are promising for rehabilitation therapies, treatment of phobias and anxiety disorders, and cognitive enhancement. Personalized VR experiences, adapted based on BCI feedback, enhance the efficacy of these interventions. This study underscores the potential for integrating VR and BCI technologies to understand and harness neuroplasticity for cognitive and therapeutic applications. The researchers utilized the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method to conduct a comprehensive and systematic review of the existing literature on neuroplasticity, VR, and BCI. This involved identifying relevant studies through database searches, screening for eligibility, and assessing the quality of the included studies. Data extraction focused on the effects of VR and BCI on neuroplasticity and cognitive functions. The PRISMA method ensured a rigorous and transparent approach to synthesizing evidence, allowing the researchers to draw robust conclusions about the potential of VR and BCI technologies in promoting neuroplasticity and cognitive enhancement.
This study performs a comprehensive bibliometric (performance analysis) and thematic content analysis of global research in "neuromarketing or consumer neuroscience" and "functional magnetic resonance imaging or fMRI." Utilizing the PRISMA framework and R package software, we analyzed thirty-six Scopus-indexed articles. The USA and California Institute of Technology emerged as leading contributors, with Rangel, A., and Reimann, M., as notable authors. Prominent themes include 'advertising,' 'product,' 'price,' and 'brand', with the “Journal of Consumer Psychology” and “Journal of Neuroscience” being key publications. The most cited article is "Marketing actions can modulate neural representations of experienced pleasantness," with 620 citations. In addition, fMRI has been used to study consumer behavior (impulsiveness, reward, emotion, decision-making, and memory) toward marketing stimuli such as price (WTP), advertising (celebrity endorsement, MSV), product (packaging design), and brand (Halal logo, label, and personality). This study provides an invaluable literature review matrix and detailed insights into the current trends in global neuromarketing research utilizing fMRI. This study highlights the significant impact of fMRI in both academic and commercial realms, offering new insights for targeted marketing and consumer behavior research. It provides valuable guidance for developing more effective advertising strategies, understanding consumer decision-making processes, enhancing business performance, and collaborating academically.
Organizations that embrace innovative business strategies position themselves well for success. In this evolving technological landscape, businesses are increasingly focused on understanding consumer behaviors and preferences to tailor their products and services effectively. Notably, integrating neuroscience has become pivotal in achieving these goals, requiring its incorporation throughout various business processes. This comprehensive research review conducts a meta-analysis, synthesizing findings from numerous studies on applying neuroscience across diverse business domains. The primary objective is to identify innovative neuroscience approaches that can significantly revolutionize businesses. Through a meticulous literature exploration using PRISMA analysis, we discerned broad themes and further refined them into critical sub-themes. This thematic categorization enables a focused examination of each area of business research. The findings in this study uncovered vital intersections between neuroscience and business, offering valuable insights for corporations and researchers. In essence, the integration of neuroscientific techniques and artificial intelligence (AI)-based softwares into business practices is no longer optional, but a necessity for businesses to stay competitive in today’s fast-paced world. This study, therefore, plays a crucial role in connecting the state-of-the-art tools and techniques in neuroscience and traditional business practices. It paves the way for a new era of business operations, where science and technology work hand in hand with commerce to create a more prosperous and sustainable future. In conclusion, the paper emphasizes the importance of incorporating neuroscience techniques and newly developed AI-based softwares into business practices. This integration can yield precise and favorable outcomes, offering businesses the tools to thrive in an ever-changing market environment.
Neuromarketing has received attention as a means to bridge the gap between conventional marketing studies and research on brain-computer interfaces based on electroencephalography (EEG). Through priority prediction, it aims to accurately determine customers' true desires. The performance of EEG-based priority detection systems relies on selecting appropriate feature extraction techniques and machine learning algorithms. Current methods do not focus on effective preprocessing techniques and the classification of EEG signals. In this study, preference detection of neuromarketing data is carried out using a combination of different EEG indicators and various algorithms for feature extraction and classification. EEG features are extracted using the discrete wavelet transform (DWT), which enhances the accuracy of priority detection for preference-based EEG indicators. Moreover, a one-dimensional convolutional neural network (CNN1D) in combination with a Long Short-Term Memory (LSTM) network is used. This study compares the proposed method with classifiers such as Support Vector Machines (SVM), Random Forest (RF) and CNN-Transformer. The results obtained demonstrate the high potential of the proposed model in the field of neuromarketing and its improvement over traditional marketing methods. This innovative approach allows us to more accurately identify unconscious consumer buying behaviors and gain a better understanding of their decision-making patterns in real purchasing situations. This study contributes to the field by demonstrating the effective use of EEG and machine learning to enhance neuromarketing strategies.
People are increasingly eager to know more about themselves through technology. To date, technology has primarily provided information on our physiology. Yet, with advances in wearable technology and artificial intelligence, the current advent of consumer neurotechnology will enable users to measure their cognitive activity. We see an opportunity for research in Human-Computer Interaction (HCI) in the development of these devices. Neurotechnology offers new insights into user experiences and facilitates the development of novel methods in HCI. Researchers will be able to create innovative interactive systems based on the ability to measure cognitive activity at scale in real-world settings. In this paper, we contribute a vision of how neurotechnology will transform HCI research and practice. We discuss how neurotechnology prompts a discussion about ethics, privacy, and trust. This trend highlights HCI’s crucial role in ensuring that neurotechnology is developed and utilised in ways that truly benefit people.
Objective: Near-misses are a structural characteristic of gambling products that can be engineered within modern digital games. Over a series of preregistered experiments using an online slot machine simulation, we investigated the impact of near-miss outcomes on subjective ratings (motivation, valence) and two behavioral measures (speed of gambling, bet size). Method: Participants were recruited using Prolific and gambled on an online three-reel slot machine simulator that delivered a one in three rate of X-X-O near-misses. Study 1 measured trial-by-trial subjective ratings of valence and motivation (Study 1a, n = 169; Study 1b, n = 148). Study 2 (n = 170) measured spin initiation latencies as a function of the previous trial outcome. Study 3 (n = 172) measured bet size as a function of the previous trial outcome. Results: In Study 1a, near-misses increased the motivation to continue gambling relative to full-misses, supporting Hypothesis 1. On valence ratings, near-misses were rated significantly more positively than full-misses, in the opposite direction to Hypothesis 2; this effect was confirmed in a close replication (Study 1b). In Study 2, participants gambled faster following near-misses relative to full-misses, supporting Hypothesis 3. In Study 3, participants significantly increased their bet size following near-misses relative to full-misses, supporting Hypothesis 4. Conclusion: Across all dependent variables, near-miss outcomes yielded statistically significant differences from objectively equivalent full-miss outcomes, corroborating the “near-miss effect” across both subjective and behavioral measures, and in the environment of online gambling. The unexpected findings on valence ratings are considered in terms of boundary conditions for the near-miss effect, and competing theoretical accounts based on frustration/regret, goal generalization, and skill acquisition.
Purpose: To develop a comprehensive overview of Neuro Management, by bridging the gap between scientific insights and effective leadership within organizational contexts based on exploring Neuro Management concepts, applications, and their implications for managerial practices. Procedure: The overview begins by delineating the fundamental concepts and applications of Neuro Management, elucidating its relevance in leveraging neuroscience principles for enhancing leadership effectiveness. It then provides an extensive overview of key themes and contributions within the field, identifying foundational works and highlighting significant research directions. A critical analysis of the evolution of Neuro Management concepts is presented, identifying existing research gaps and tracing the evolutionary trajectory of the field. Furthermore, a conceptual framework is developed, integrating neuroscience principles with leadership practices, and delineating a structured approach for applying neuroscience insights in leadership contexts. Analysis: The paper discusses the neural mechanisms underlying various aspects related to Neuro Management, exploring decision-making processes, emotional intelligence, and their neural correlates. Subsequently, it analyzes how Neuro Management concepts bridge the gap between scientific insights and effective leadership, highlighting the translation of neuroscience findings into practical leadership strategies. Moreover, the implications of Neuro Management for organizational practices, decision-making, team dynamics, and productivity are expounded upon, emphasizing its transformative impact on enhancing organizational performance. The study assesses the connection between human productivity and Neuro Management, focusing on how Neuro Management strategies affect organizational effectiveness. The study also critically analyzes leadership and neuro management from a managerial perspective, evaluating their effects on organizational outcomes and their roles in decision-making. Additionally, it explores how different Neuro Management models that are helpful in decision science might be applied to create efficient decision-making processes. Furthermore, the paper adopts an ABCD listing framework, analyzing Neuro Management from Managers' Points of View, evaluating its Advantages, Benefits, Constraints, and Disadvantages. Finally, it suggests postulates for future research and practical applications in Neuro Management, emphasizing areas warranting further exploration and implementation. Originality/Value: This comprehensive overview aims to serve as a foundational resource in the expanding field of Neuro Management, offering insights, analyses, and frameworks for advancing leadership practices informed by neuroscience principles. Type of Paper: Conceptual exploratory research.
With the development of intelligent transportation, it has become mainstream for drivers and automated systems to cooperate to complete train driving tasks. Human-machine trust has become one of the biggest challenges in achieving safe and effective human-machine cooperative driving. Accurate evaluation of human-machine trust is of great significance to calibrate human-machine trust, realize trust management, reduce safety accidents caused by trust bias, and achieve performance and safety goals. Based on typical driving scenarios of high-speed trains, this paper designs a train fault judgment experiment. By adjusting the machine’s reliability, the driver’s trust is cultivated to form their cognition of the machine. When the driver’s cognition is stable, data from the Trust in Automated (TIA) scale and modes of physiological information, including electrodermal activity (EDA), electrocardiograms (ECG), respiration (RSP), and functional near-infrared spectroscopy (fNIRS), are collected during the fault judgment experiment. Based on analysis of this multi-modal physiological information, a human-machine trust classification model for high-speed train drivers is proposed. The results show that when all four modes of physiological information are used as input, the random forest classification model is most accurate, reaching 93.14%. This indicates that the human-machine trust level of the driver can be accurately represented by physiological information, thus inputting the driver’s physiological information into the classification model outputs their level of human-machine trust. The human-machine trust classification model of high-speed train drivers built in this paper based on multi-modal physiological information establishes the corresponding relationship between physiological trust and human-machine trust level. Human-machine trust level is characterized by physiological trust monitoring, which provides support for the dynamic management of trust.
In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales—from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration, and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues, and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research.
In recent years, the scientific community has begun tо explore the efficacy оf an integrated neurofeedback + biofeedback approach іn various conditions, both pathological and non-pathological. Although several studies have contributed valuable insights into its potential benefits, this review aims tо further investigate its effectiveness by synthesizing current findings and identifying areas for future research. Our goal іs tо provide a comprehensive overview that may highlight gaps іn the existing literature and propose directions for subsequent studies. The search for articles was conducted on the digital databases PubMed, Scopus, and Web of Science. Studies to have used the integrated neurofeedback + biofeedback approach published between 2014 and 2023 and reviews to have analyzed the efficacy of neurofeedback and biofeedback, separately, related to the same time interval and topics were selected. The search identified five studies compatible with the objectives of the review, related to several conditions: nicotine addiction, sports performance, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD). The integrated neurofeedback + biofeedback approach has been shown to be effective in improving several aspects of these conditions, such as a reduction in the presence of psychiatric symptoms, anxiety, depression, and withdrawal symptoms and an increase in self-esteem in smokers; improvements in communication, imitation, social/cognitive awareness, and social behavior in ASD subjects; improvements in attention, alertness, and reaction time in sports champions; and improvements in attention and inhibitory control in ADHD subjects. Further research, characterized by greater methodological rigor, is therefore needed to determine the effectiveness of this method and the superiority, if any, of this type of training over the single administration of either. This review іs intended tо serve as a catalyst for future research, signaling promising directions for the advancement оf biofeedback and neurofeedback methodologies.
Educators have been increasingly focused on the concept of educational leadership in the context of global educational reform. With the emergence of neuroscience, there is potential to further explore the theory and practice of educational leadership from a neuroscience perspective. This article provides an overview of the neuroscience research related to educational leadership, including leadership traits, styles, decision‐making, and contingency perspectives. Additionally, the article examines the application of neuroscience in the assessment and enhancement of educational leadership with the goal of providing useful insights.
Scholars and managers have long discussed the best profile for successful leadership, which can influence employee performance and organizational growth. Despite leadership being the focus of many studies and continuous training, what explains leaders’ effectiveness within institutions and companies remains unclear. To better understand this phenomenon, we perform a comprehensive review of empirical studies and theoretical essays (N = 93) exploring the application of neuroscience in an organization’s practices and leaders’ development. We conducted a systematic review using these references and built narrative arguments organizing understudied areas and defining a process to classify and integrate trends. The study is different from previous research in identifying groups of research areas such as the biological, brain, psychological, management, emotional, and cognitive approaches, as well as research topics such as culture, decision-making, engagement, ethics, and human development. Moreover, we suggest a theoretical framework comprising those approaches and the main research topics to stimulate the move of the field forward. The article contributes to the literature by organizing the state of the art of research and presenting neuroleadership as a construct. We conclude with suggestions for future research that we hope will address existing gaps and contribute to building relevant theories and policy recommendations.
Although neuromarketing research has developed, the current studies lack to provide comprehensive insights into neuromarketing and marketing mix. Therefore, this study has designed to provide a comprehensive overview of neuromarketing, classification of neuroimaging and physiological tools are currently used in the marketing mix, and highlights the neural responses of consumer’s behavior (e.g., emotions, attention, motivation, reward processing, and perception) to be considered in the marketing mix. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to select relevant documents for this article. In this study, 106 articles and review papers were extracted and analyzed from the Web of Science database to fill the gap in the literature. We found that 10 tools have been used in studying the marketing mix, such as advertising, brand, price, and product). For example, electroencephalography was the most applied tool, while advertising was the most marketing mix employed. We also found that the frontal and temporal gyri were correlated with pleasure/displeasure and high/low arousal. The occipital lobe is linked to attention processes, while the hippocampus relates to long and short-term memory. Such findings provide valuable insights into the neural responses in marketing mix research.
The driver is one of the most important factors in the safety of the transportation system. The driver’s perceptual characteristics are closely related to driving behavior, while electroencephalogram (EEG) as the gold standard for evaluating human perception is non-deceptive. It is essential to study driving characteristics by analyzing the driver’s brain activity pattern, effectively acquiring driver perceptual characteristics, creating a direct connection between the driver’s brain and external devices, and realizing information interchange. This paper first introduces the theories related to EEG, then reviews the applications of EEG in scenarios such as fatigue driving, distracted driving, and emotional driving. The limitations of existing research have been identified and the prospect of EEG application in future brain-computer interface automotive assisted driving systems have been proposed. This review provides guidance for researchers to use EEG to improve driving safety. It also offers valuable suggestions for future research.
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that provides a pathway between the brain and external devices by interpreting EEG. EEG-based BCI applications have initially been developed for medical purposes, with the aim of facilitating the return of patients to normal life. In addition to the initial aim, EEG-based BCI applications have also gained increasing significance in the non-medical domain, improving the life of healthy people, for instance, by making it more efficient, collaborative and helping develop themselves. The objective of this review is to give a systematic overview of the literature on EEG-based BCI applications from the period of 2009 until 2019. The systematic literature review has been prepared based on three databases PubMed, Web of Science and Scopus. This review was conducted following the PRISMA model. In this review, 202 publications were selected based on specific eligibility criteria. The distribution of the research between the medical and non-medical domain has been analyzed and further categorized into fields of research within the reviewed domains. In this review, the equipment used for gathering EEG data and signal processing methods have also been reviewed. Additionally, current challenges in the field and possibilities for the future have been analyzed.
Train drivers’ inattention, including fatigue and distraction, impairs their ability to drive and is the major risk factor for human-caused train accidents. Many experts have undertaken numerous studies on train driver exhaustion and distraction, but a systematic study is still missing. Through a systematic review, this work aims to outline the types, risk factors, consequences, and detection methods of train driver fatigue and distraction. The effects of central nervous fatigue and cognitive distraction in train drivers during driving are caused by rest and sleep schedules, workload, automation levels, and mobile phones. Furthermore, train drivers’ fatigue and distraction can cause loss of concentration and slow reaction, resulting in dangerous driving behaviour such as speeding and SPAD. Researchers have combined subjective reporting, physiological parameters, and physical factors to construct detection algorithms with good results to detect train driver fatigue and distraction. This review offers recommendations for researchers looking into train driver fatigue and distraction. And it can also make valuable recommendations for future studies about railway traffic safety.
ocial media addiction is a growing problem throughout the world. It has been characterized as a type of behavioral addiction, which can be measured using standardized criteria based on six general properties of addiction criteria: salience, mood modification, tolerance, withdrawal symptoms, conflict and relapse. Several studies have found a prevalence of approximately 10% for social media addiction in individuals across the globe, indicating that this problem is common and widespread. Deleterious effects of this disorder include depressive symptoms, increased anxiety, and a lowered sense of personal well-being. Social media addiction also has been linked to neuroplastic changes that diminish attention and impede an individual’s ability to focus. There many dimensions of social media that can foster addiction, including the exploitation of evolutionarily old urges to communicate and socialize, as well as intentional design of the user interface to hook users into constant use. There is little doubt that social media companies are financially incentivized to maximize user attentiveness to ads (i.e., ad views and clicks) on their platforms because user attention is the product for which they are paid. These companies maximize user attentiveness in two primary ways: first, by intentionally designing the interface to have properties intended to hold users’ attention; and second, by personalizing the content shown to users in order to make it more interesting and engaging for them. Social media addiction likely arises from the vicious cycle involving user attention leading to powerful dopamine-related reinforcement, which then stimulates more attention intended to achieve more reinforcement. This paper provides an overview of this multifaceted problem of social media addiction, including a brief review of addictions in general, social media addiction in particular, and a discussion of the prevalence and consequences of this addiction. Also discussed is the role social media companies play in addiction by design, along with the critical need to present solutions to social media addiction. These solutions, beginning with redesign of the user interface properties to make them more humane and ethical, are possible, but will not be easy. However, we all must work toward a world in which people use technology for their own well-being rather than for the well-being of those who control the technology.
Purpose
This study focuses on the role of individuals in the innovation management process, by concentrating on leaders and associated behaviors. Specifically, Entrepreneurial Leadership (EL) represent one of the most important fields of innovation management that has become increasingly multifaceted and interdisciplinary with its evolution. Thus, the purpose of this study is to examine a newly emerging research trend with a new lens that is “neuroscience”.
Design/methodology/approach
This paper finds an evidence-based roadmap by reviewing the literature with a quantitative Bibliometric Analysis (BA) employing Co-Citation (Co-C) and bibliographic coupling analysis (BcA) to find linkages between the leadership and entrepreneurship literature and the neuroscience literature.
Findings
This study identifies five promising groups of research areas such as the organizational approach, the biological approach, the cognitive approach, the emotional approach and it identify five future research topics such as dynamic skills in innovation exploitation process, the human aspect of leadership, the building process of leadership, the biological perspective of leadership and the application of neuroscience in the ecosystem. Moreover, we find an evidence-based roadmap for stimulating focused EL within the broad topic of innovation management research, to move the field forward.
Originality/value
Although the past few years have observed the necessity of review studies on the subsets of biological factors, no reviews have sought to bring those different subsets together into a broader biological perspective. This study provides important indications on the interdisciplinary developments between the neuroscience aspects and EL, as a new emerging paradigm within the broad field of innovation management.
Fueled by early success stories, the neuromarketing domain advanced rapidly during the last 10 years. As exciting new techniques were being adapted from medical research to the commercial domain, many neuroscientists and marketing practitioners have taken the chance to exploit them so as to uncover the answers of the most important marketing questions. Among the available neuroimaging technologies, electroencephalography (EEG) stands out as the less invasive and most affordable method. While not equally precise as other neuroimaging technologies in terms of spatial resolution, it can capture brain activity almost at the speed of cognition. Hence, EEG constitutes a favorable candidate for recording and subsequently decoding the consumers' brain activity. However, despite its wide use in neuromarketing, it cannot provide the complete picture alone. In order to overcome the limitations imposed by a single monitoring method, researchers focus on more holistic approaches. The exploitation of hybrid EEG schemes (e.g., combining EEG with eye-tracking, electrodermal activity, heart rate, and/or other) is ever growing and will hopefully allow neuromarketing to uncover consumers' behavior. Our survey revolves around last-decade hybrid neuromarketing schemes that involve EEG as the dominant modality. Beyond covering the relevant literature and state-of-the-art findings, we also provide future directions on the field, present the limitations that accompany each of the commonly employed monitoring methods and briefly discuss the omni-present ethical scepticizm related to neuromarketing.
The capability of monitoring user’s performance represents a crucial aspect to improve safety and efficiency of several human-related activities. Human errors are indeed among the major causes of work-related accidents. Assessing human factors (HFs) could prevent these accidents through specific neurophysiological signals’ evaluation but laboratory sensors require highly-specialized operators and imply a certain grade of invasiveness which could negatively interfere with the worker’s activity. On the contrary, consumer wearables are characterized by their ease of use and their comfortability, other than being cheaper compared to laboratory technologies. Therefore, wearable sensors could represent an ideal substitute for laboratory technologies for a real-time assessment of human performances in ecological settings. The present study aimed at assessing the reliability and capability of consumer wearable devices (i.e., Empatica E4 and Muse 2) in discriminating specific mental states compared to laboratory equipment. The electrooculographic (EOG), electrodermal activity (EDA) and photoplethysmographic (PPG) signals were acquired from a group of 17 volunteers who took part to the experimental protocol in which different working scenarios were simulated to induce different levels of mental workload, stress, and emotional state. The results demonstrated that the parameters computed by the consumer wearable and laboratory sensors were positively and significantly correlated and exhibited the same evidences in terms of mental states discrimination.
If platforms such as Facebook, Instagram, and Twitter are the engines of social media use, what is the gasoline? The answer can be found in the psychological dynamics behind consumer habit formation and performance. In fact, the financial success of different social media sites is closely tied to the daily‐use habits they create among users. We explain how the rewards of social media sites motivate user habit formation, how social media design provides cues that automatically activate habits and nudge continued use, and how strong habits hinder quitting social media. Demonstrating that use habits are tied to cues, we report a novel test of a 2008 change in Facebook design, showing that it impeded posting only of frequent, habitual users, suggesting that the change disrupted habit automaticity. Finally, we offer predictions about the future of social media sites, highlighting the features most likely to promote user habits.
In this article we will report on the application to the business context of the Brain Wellness program, a technology-driven service that aims to enhance the cognitive abilities and performance of people in the workplace using methods that are based on neuroscientific research. The neurotechnologies used in the Brain Wellness program are three. The Lifestyle Assessment Lab, by measuring with a biofeedback sensor the heart rate (HR) and its variability (HRV) over 24 hours, tracks some important parameters about the person’s lifestyle, like the sleep quality, the stress-recovery balance and the effect of physical activity. The Mindfulness Lab aims to enhance the work performance of people by decreasing their level of stress and anxiety through the exercise of awareness and attention on a digital platform and group coaching sessions. The Cognitive Training Lab aims to enhance people’s work performance through executive function exercises.
The integration of quantum AI and neuromarketing heralds a new direction in the analysis and forecast of consumer behavior. MRI and EEG techniques were beneficial in discovering the structural paths involved in decisions, but quantum AI enhances the accuracy and data analysis depth to decoding the underlying consumers' responses. Relatively, this chapter explains the historical development of neuromarketing, incorporating basic ideas in quantum computing and its relevance in marketing. To illustrate this approach we examine real world, practical applications and how these innovative tools are being used to create unique messaging that appeals to the emotions and effective reasoning of the consumer. The chapter also includes discussions on other concerns linked to the utilization of such strong technologies, relating to privacy and autonomy. With quantum AI on the rise for future developments in consumer behavior analysis, it is important for the researchers, marketers, and policymakers to follow a structured approach which is made available in this chapter.
This chapter reviews neuromarketing and AI interaction, especially related to sophisticated decision-making techniques that provide better insights into the phenomenon of consumer behavior. Neuromarketing incorporates neuroscience into marketing strategies to analyze subconscious reactions to achieve a level of understanding beyond traditional means such as surveys. Neuromarketing in the world of digital era lies in the complexity of the consumer structure where fast decisions are made unconsciously. Amongst the three key benchmark decision-making methods-neural networks, fuzzy decision-making and evolutionary algorithms-the three represent processing complex data, incorporating subtle consumer preferences, and continuously optimizing marketing strategies within iterative feedback loops. An AI-driven decision making conceptualizes a holistic approach to data gathering using neuromarketing tools, feature extraction with neural networks, and decision optimization through fuzzy logic and evolutionary algorithms.
When we use language to communicate, we must choose what to say, what not to say, and how to say it. That is, we must decide how to frame the message. These linguistic choices matter: Framing a discussion one way or another can influence how people think, feel, and act in many important domains, including politics, health, business, journalism, law, and even conversations with loved ones. The ubiquity of framing effects raises several important questions relevant to the public interest: What makes certain messages so potent and others so ineffectual? Do framing effects pose a threat to our autonomy, or are they a rational response to variation in linguistic content? Can we learn to use language more effectively to promote policy reforms or other causes we believe in, or is this an overly idealistic goal? In this article, we address these questions by providing an integrative review of the psychology of framing. We begin with a brief history of the concept of framing and a survey of common framing effects. We then outline the cognitive, social-pragmatic, and emotional mechanisms underlying such effects. This discussion centers on the view that framing is a natural—and unavoidable—feature of human communication. From this perspective, framing effects reflect a sensible response to messages that communicate different information. In the second half of the article, we provide a taxonomy of linguistic framing techniques, describing various ways that the structure or content of a message can be altered to shape people’s mental models of what is being described. Some framing manipulations are subtle, involving a slight shift in grammar or wording. Others are more overt, involving wholesale changes to a message. Finally, we consider factors that moderate the impact of framing, gaps in the current empirical literature, and opportunities for future research. We conclude by offering general recommendations for effective framing and reflecting on the place of framing in society. Linguistic framing is powerful, but its effects are not inevitable—we can always reframe an issue to ourselves or other people.
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: Long monotonous driving tasks can induce driver fatigue, significantly reducing vigilance and threatening the safety of high-speed train operations. Despite the importance of addressing this issue, effective interventions to mitigate driver fatigue in the context of high-speed railway systems remain a challenge. This study aims to examine the effects of three tactile intervention strategies (transcutaneous electrical acupoint stimulation, thermal stimulation, and vibration stimulation) on alleviating driver fatigue.
Methods
: A high-speed train simulator was used to conduct experiments with subjects. Each participant was required to complete four driving tasks: one without any intervention and three with each of the aforementioned tactile interventions when experiencing fatigue. Physiological metrics such as reaction time, electrocardiogram (ECG), and electroencephalogram (EEG) were collected to assess driver vigilance.
Findings
: The results revealed that thermal and vibration stimulations effectively reduced reaction times (TS = 1.11s, VS = 1.09s, no-intervention = 1.12s) and slowed down the fatigue process. Drivers exhibited higher vigilance levels during these interventions, as reflected in improved ECG and EEG features. For example, the high-frequency energy of the EEG signal increases during the stimulation compared to before the stimulation. However, transcutaneous electrical acupoint stimulation did not show significant effects on fatigue reduction.
Novelty
: This study contributes to the literature by providing evidences to support that appropriate tactile interventions, particularly thermal and vibration stimulations, can effectively mitigate driver fatigue and improve vigilance levels. These findings offer practical insights for enhancing the safety of high-speed railway operations by minimizing risks associated with driver fatigue.
There is a transformation from the traditional practices in integrating neurotechnology into Human Resource Management (HRM) which will optimize employee performance and well-being. Neurotechnologies provide profound insights into cognitive and emotional processes. These tools offer HR professionals the ability to assess the cognitive load, stress levels, and attention in real-time, informing strategic decision-making and personalized HR strategies. This chapter explores the multifaceted applications of neurotechnology in HRM, focusing on recruitment and selection processes. By leveraging neurotechnological tools, organizations can gain objective measures of candidates' cognitive and emotional traits, enhancing the precision and predictive power of recruitment decisions.
For years, Human Resource Development and Management (HRDM) has used behavioral assessments to gauge employee potential. However, advancements in cognitive behavioral neuroscience (CBN) have opened up new possibilities for understanding how the human mind works. This chapter explores the practical applications of neuroscience methods like EEG, ERP, MRI, and fMRI, as well as neurofeedback and biofeedback, in talent identification, leadership development, and employee well-being. Importantly, these insights can be directly applied in HRDM practices, leading to more effective talent management, leadership development, and improved employee well-being. While recognizing the ethical considerations involved with these technologies, the chapter presents a compelling vision for a future where HRDM practices are informed by a deeper understanding of the brain, enabling the workforce to reach its full potential.
Neuroleadership has emerged as a field combining neuroscience and leadership. It has gained increasing attention recently, attracting interest from academics, researchers, and practitioners. It refers to the brain functions that affect leadership abilities and how they make decisions and solve problems. Cognitive enhancement with neurofeedback and neurological assessment tools are discussed. Though evolving, virtual reality/augmented reality (VR/AR) is helping with real-time neural data. All these tools are helping organizations in their leadership with neuroscience optimizing leadership behaviors and decision-making. Organizations must build strategies for using available research to implement neuroleadership, learn from the adoption, refine them, and then future-proofing leadership practices. Several methodological issues will be encountered in the research journey, but by staying focused and constantly optimizing, the organizations can decide what works best for them. The ethical use of tools and methods and the regulatory restrictions are to be watched.
Workplace stress is a common issue that can significantly impact both employees and employers. This study explores the dynamic intersection of workplace stress and the emerging field of neuroleadership, offering insights into fostering resilient work environments. Drawing on the principles of neuroleadership, the chapter highlights how an understanding of neuroscience can inform leadership practices and contribute to creating resilient workplaces. This chapter discusses the neurological basis of stress and the role of leaders in mitigating its effects. It explores emotional intelligence in leadership and the impact of organisational culture on stress resilience. The chapter suggests practical interventions like mindfulness practices and supportive work environment initiatives grounded in neuroscience to cultivate a culture of wellbeing. By adopting resilient leadership strategies and understanding the neuroscience of stress, organisations can create environments that promote employee wellbeing and navigate the challenges of the modern workplace.
This chapter assesses neuroscience, related technologies and applications, and its implications for organisational studies and management. It also reviews neuroscientific tools to understand the neural features of management decision-making and customer/consumer behaviour, its origins, and underlying principles. For this purpose, the chapter starts with a brief overview and history of neuroscience, its use in organisations, and a subsequent focus on the technology driving neuroscience and, simultaneously, the latest developments in this developing discipline. After revealing the different implications in organisations, particularly in management and strategy, leadership, marketing, and economics, it will next point out emerging ethical and philosophical challenges and debates in neuroscience in organisational studies that emerged throughout its development. The chapter will end by addressing potential future implications and research directions for neuroscience in organisations and drawing conclusions.
The aim of this work is to register and analyse, using neurotechnology, in onsite onsite and online university educational context, the effect on relevant variables in the learning process. This represents an innovation in the current academic literature in this field. In this study, neuroscience technology has been used to measure the cognitive processing of stimuli designed for an academic experience in a university master's degree class. The neurotechnologies employed were galvanic skin response (GSR), electroencephalography (EEG) and eye tracking. After the analysis of the brain recordings, based on attention, interest, stress and engagement in an onsite educational context and their comparative analysis with the online monitoring, the results indicated that the levels of emotional intensity of the students who followed the class in person were higher than those who attended online. At the same time, the values of positive brain activity (attention, interest and engagement) were higher in the onsite group, and the negative variable stress was also higher, which could be explained by the fact that the online students did not activate the camera. The brain recordings of students who were distance learning show less interest and attention, as well as less emotional intensity, demonstrating that distance (online) learning is less effective than classroom learning, in terms of brain signals, for a theoretical university master's degree class.
Influential learning-based accounts of substance addictions posit the attribution of incentive salience to drug-associated cues, and its escalation by the direct dopaminergic effects of drugs. In translating this account to disordered gambling, we have noted how the intermittent nature of monetary rewards in gambling (i.e. the variable ratio) may allow for analogous learning processes, via effects on dopaminergic signalling. The aim of the present article is to consider how multiple sources of reward variability operate within modern gambling products, and how similar sources of variability, as well as some novel sources of variability, also apply to other digital products implicated in behavioural addictions, including gaming, shopping, social media and online pornography. Online access to these activities facilitates not only unparalleled accessibility but also introduces novel forms of reward variability, as seen in the effects of infinite scrolls and personalized recommendations. We use the term uncertainty to refer to the subjective experience of reward variability. We further highlight two psychological factors that appear to moderate the effects of uncertainty: 1) the timecourse of uncertainty, especially with regard to its resolution, 2) the frequency of exposure, allowing temporal compression. Collectively, the evidence illustrates how qualitative and quantitative variability of reward can confer addictive potential to non-drug reinforcers by exploiting the psychological and neural processes that rely on predictability to guide reward seeking behaviour.
GET READY: Neurotechnology is coming to the workplace. Neural sensors are now reliable and affordable enough to support commercial pilot projects that extract productivity-enhancing data from workers' brains. These projects aren't confined to specialized workplaces; they're also happening in offices, factories, farms, and airports. The companies and people behind these neurotech devices are certain that they will improve our lives. But there are serious questions about whether work should be organized around certain functions of the brain, rather than the person as a whole.
Recent educational trends point to an interest in educational neurotechnology. While these tools have the potential to change education, little is known about whether their use improves educational outcomes. Additionally, their adoption may be negatively impacted by teachers’ lack of knowledge about the brain. In this paper we outline the potential of educational neurotechnology including what we know, what we do not yet know, and additional considerations for the ethical, successful adoption of these tools in classrooms around the world. Special consideration is given to the training needs of pre- and in-service educators whose support will be essential to the successful adoption of educational neurotechnology.
Emotions are essential in today's complex information environments, as they catch readers' attention and impact the depth of information processing. In online interactions - such as user comments on social media platforms - emotions are increasingly present. We performed a preregistered eye-tracking study to understand the effects of emotional user comments on attention. Participants (N = 155) in our study read a series of user comments with different emotional tones. We measured the effects of emotions on information processing and visual attention by comparing the dwell times of participants of two experimental groups: a heuristic processing group and a systematic processing group. Our results revealed differences in visual attention towards comments with a negative versus positive valence and between the discrete emotions of anger and fear. These findings lead to a discussion about emotions' role in information processing when individuals read user comments on social media.
Previous interactive marketing literature has concluded that banner attributes are key drivers of ad effectiveness and online consumer behaviors. In particular, prior advertising studies have largely defined the two most commonly used ad appeals in online settings: hedonic (i.e., visually attractive, joy-focused, and interactive) and utilitarian (i.e., informative, convenient, and functional). However, no unanimous conclusions have been drawn about their effects on online consumer behavior. Furthermore, no studies have assessed the psychological mechanisms underlying the processing of hedonic and utilitarian banner ads, which could be crucial given the unconscious, internal, and introspective nature of ad evaluation and online purchasing decisions. In this research, the authors used neuroimaging (functional magnetic resonance imaging [fMRI]) to identify the neural mechanisms underlying the evaluation of hedonic and utilitarian banners. The results reveal that whereas hedonic layouts engage brain areas associated with reward, self-relevance, and emotion, utilitarian banner ads trigger brain networks related to object identification and recognition, reasoning, executive function, and cognitive control. This research also examines the extent to which neural data derived from processing hedonic and utilitarian banners complement the ability of self-reported banner effectiveness to predict online consumer behavior. The results reveal that neural data from banner appeals help predict between 9% and 18% of online consumer behavior beyond that indicated by the perceived ad effectiveness reported by consumers. Taken together, these results provide new insights into the connection between neuropsychological data and real-world online consumer behavior.
Neuromarketing is the application of neuroscience to the understanding of consumer preferences towards products and services. As such, it studies the neural activity associated with preference and purchase intent. Neuromarketing is considered an emerging area of research, driven in part by the approximately 400 billion dollars spent annually on advertisement and promotion. Given the size of this market, even a slight improvement in performance can have an immense impact. Traditional approaches to marketing consider a posteriori user feedback in the form of questionnaires, product ratings, or review comments, but these approaches do not fully capture or explain the real-time decision making process of consumers. Various physiological measurement techniques have been proposed to facilitate the recording of this crucial aspect of the decision making process, including brain imaging techniques (Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), Steady State Topography (SST)) and various biometric sensors. The use of EEG in neuromarketing is especially promising. EEG detects the sequential changes of brain activity, without appreciable time delay, needed to assess both the unconscious reaction and sensory reaction of the customer. Several types of EEG devices are now available in the market, each with its own advantages and disadvantages. Researchers have conducted experiments using many of these devices, across different age groups and different categories of products. Because of the deep insights that can be gained, the field of neuromarketing research is carefully monitored by consumer and research protection groups to ensure that subjects are properly protected. This paper surveys a range of considerations for EEG-based neuromarketing strategies including, the types of information that can be gathered, how marketing stimuli are presented to consumers, how such strategies may affect the consumer in terms of appeal and memory, machine learning techniques applied in the field, and the variety of challenges faced, including ethics, in this emerging field.
International business research posits that, under certain circumstances, consumers prefer goods manufactured in their own country regardless of their country of origin image. Yet the psychological origin of such Domestic bias remains unknown. This study presents a neuroimaging experiment developed in Spain. The task combined low and high involvement goods marked with Domestic “Made in Spain” and Foreign “Made in USA” (similar culture) and “Made in China” (different culture) labels. The findings reveal that Domestic goods always convey neural rewarding sensations. Neural aversive biases toward Foreign goods occur only when the products are culturally different and high involvement. These findings help improve business retailing strategies.