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Purpose This paper aims to clarify the relationship between multiple intelligence (MI) and entrepreneurial opportunity recognition. It discusses to what extent each dimension of MI is considered as an activation driver of entrepreneurial opportunities recognition. This paper also aims to expand the domain of entrepreneurial opportunities recognition via MI by considering the mediating role of neuromarketing perception, adopting a combined perspective of intelligence, entrepreneurship and also neuromarketing to provide a future direction for the creation of interdisciplinary insights in the area of entrepreneurship. Design/methodology/approach This paper opted for literature synthesis to define key concepts surrounding MI and entrepreneurial opportunities recognition. Besides, it also attempted to identify an influential mediator in explaining the entrepreneurial opportunities recognition phenomenon. Consequently, this paper identified the gaps in current research to draw upon a more holistic conceptual framework. The rationale for the research was justified within the body of research. Findings This paper suggested research propositions based on the literature synthesis in view of MI and entrepreneurial opportunities recognition. More specifically, it has proposed a conceptual framework, explaining the relationship between a multi-dimensional view of both MI and entrepreneurial opportunities recognition. It is envisaged that the mediating role of neuromarketing perception incorporated in this conceptual work will improve the predictive value of the proposed framework and offer additional insights about factors that advance entrepreneurial opportunities recognition. Research limitations/implications This paper suffers from the obvious limitation of lacking empirical investigation. However, it does provide a theoretical rationale for the argument that entrepreneurial opportunities recognition can be advanced if MI are identified and associated with neuromarketing dimensions. Perhaps the most important direction for future research is further extension and validation of this framework by performing an empirical investigation to produce newer insights into this phenomenon. Originality/value This conceptual work is different from previous studies on the grounds it has considered unexplored issues in explaining entrepreneurial opportunities recognition. To bridge the critical knowledge gap of the entrepreneurial opportunities recognition phenomenon, a mediating effect of neuromarketing perception is also integrated within the model. The proposed model was neither formulated nor tested empirically in previous studies locally or perhaps globally, therefore it stands out as an original contribution incorporating MI and entrepreneurial opportunities recognition phenomenon while considering the brain activity through neuromarketing perception.

A basic aim of marketing research is to predict consumers’ preferences and the success of marketing campaigns at the population-level. However, traditional marketing tools have various limitations, calling for novel measures to improve predictive power. In this study, we use multiple types of measures extracted from electroencephalography (EEG) recordings and machine learning (ML) algorithms to improve preference prediction based on self-reports alone. Subjects watched video commercials of six food products as we recorded their EEG activity, after which they responded to a questionnaire that served as a self-report benchmark measure. Thereafter, subjects made binary choices over the food products. We attempted to predict within-sample and population level preferences, based on subjects’ questionnaire responses and EEG measures extracted during the commercial viewings. We reached 68.5% accuracy in predicting between subjects’ most and least preferred products, improving accuracy by 4.07 percentage points compared to prediction based on self-reports alone. Additionally, EEG measures improved within-sample prediction of all six products by 20%, resulting in only a 1.91 root mean squared error (RMSE) compared to 2.39 RMSE with questionnaire-based prediction alone. Moreover, at the population level, assessed using YouTube metrics and an online questionnaire, EEG measures increased prediction by 12.7% and 12.6% respectively, compared to only a questionnaire-based prediction. We found that the most predictive EEG measures were frontal powers in the alpha band, hemispheric asymmetry in the beta band, and inter-subject correlation in delta and alpha bands. In summary, our novel approach, employing multiple types of EEG measures and ML models, offers marketing practitioners and researchers a valuable tool for predicting individual preferences and commercials’ success in the real world.

In the last decade, the new means of communication have determined substantial changes in human behavior and in the way individuals interact with each other. Besides the numerous benefits and opportunities that have arisen throughout the digitalization process, both for individuals as well as for private companies and state institutions, the widespread use of the Internet has generated vulnerabilities and threats. One of the most consistent concerns related to the new means of communication, especially social media platforms, refers to fake news. In recent years, major events including the 2016 presidential election in the US, Brexit, and the emergence of the COVID-19 pandemic have proven the negative effects of fake news on society. In this paper, we use an eye-tracking experiment to determine the unconscious reactions of consumers regarding the attraction potential of a fake news manner written article about a celebrity couple. The results of the experiment for this magazine’s article, with a fake title about the celebrity couple, show that the participants focus their attention on celebrities and fake titles mostly. The picture of the celebrities and the fake title of the article beats the other areas from the article and less on the information in the text. The research proves empirically that consumers are more attentive to celebrity pictures and fake breaking news titles and less to real information in the article. To sum up, testimonials and fake news play an important role in attracting publicity and influencing consumer behavior.

PurposeThe main goal of this paper is to systematically evaluate the bibliographic production on neuromarketing from 1945 to 2018, with an emphasis on consumer behavior, to identify possible convergence of interests among health and marketing fields.Design/methodology/approachThis article was based on a systematic literature review (SLR) with the intention of investigating research related to neuromarketing by means of network analysis of citations.FindingsThe research reveals that there are formed networks in the health and management areas, but they are insufficient to enhance the neuromarketing results. Ethics has been mentioned in some studies, but the maps do not suggest that it is a developing field. Similar results can be seen within the sales area that can be capitalized on by research of gains related to consumer behavior.Research limitations/implicationsOne limitation of this study was the use of only one database (Web of Science®) that published several works from 1945 to the present time, but certainly has not exhausted the possibilities of research in the area.Originality/valueThis article helped to highlight the importance of ethics in clinical and business processes using neuroimaging, which could be an easy way to understand the behavioral and physiological mechanisms.

As a result of technological and information development, there is a rapid spread of neurotechnology in the advertising industry, which sparks debate among law and marketing scholars regarding ethics, reasonability and legality of their use. The paper aims to identify possible ways to increase the effectiveness of regulatory and ethical aspects of using neurotechnology in Ukraine’s advertising industry. Based on a systematic analysis of theoretical experience and regulatory legal acts, the main threats to the development of neuromarketing are identified. The lack of a neurotechnology law, the distinguishing between “neuro data” and “personal data”, cyber-hacking risks, the lack of an interaction model between the state and advertisers are deemed to be regulatory shortcomings. Possible ways to optimize the legal regulation of the neurotechnology use are the development of a neurotechnology law, the legislative enshrinement of the neuro data concept, the introduction of restrictions on neuro data use depending on the industry and purpose, increased cybersecurity level. Threats to the ethical use of neurotechnology include low public awareness of neurotechnology and personal rights of citizens, lack of training activities for marketers and advertisers in the field of neuroscience. It is possible to overcome ethical threats through educational and informational work for marketers, advertisers and citizens. A comprehensive solution to the ethical and legal shortcomings of neurotechnology use will increase the neurotechnology development level, the proficiency level of marketers and advertisers, as well as improve the legal system in Ukraine.

Marketing in social media is gaining importance among young consumers. Because of the clutter in social network services (SNS) like Facebook, creating engaging content that can generate click-through and sharing behaviors is becoming a key success factor for SNS marketing. We investigate the neural indicators of engagement with content as a driver of consumers′ click-through behavior in social media. Using a novel neuroscientific research methodology called event-related potentials (ERP), we find unique brainwave signals that combine P3 and late positive potential (LPP), increasing power signals with multiple exposures while young consumers are exposed to highly engaging Facebook posts. These unique brainwave signals in response to engagement with online content, which occur within 300 ms, are detected in the bilateral temporal brain areas. A new neuromarketing method will soon allow marketers to predict consumers′ online click-through behaviors from micro-second brain processes that occur almost simultaneously with the time of content exposure.

Brain–computer interface (BCI) technology used to monitor conscious-brain electrical activity via electroencephalogram (EEG) signals has facilitated the detection of human preferences. Recently, great progress has been made in the development of novel paradigms and methods for EEG-based preference detection including attempts to apply BCI research findings in various contexts. Advances in BCI technology have increased the scientists’ interest in possible practical applications of BCI technology involving a human–machine interaction. A major objective of our research was to provide an overview of recent advances in EEG-based preference detection applications. As a foundation for our research, we reviewed previous studies in EEG-based neuromarketing and classified them according to their practical domains, research directions, and recording modalities. Another major research goal was to investigate how the analysis of EEG signals using classification algorithms can be applied to recognize and understand consumers’ mental states and preferences patterns. To this end, we built three different classification algorithms: the random forest (RF), support vector machine (SVM), and the k-nearest neighbor (KNN). Our results demonstrate that RF is more accurate than either KNN or SVM.

El avance de la tecnología permite el uso de nuevas herramientas en las investigaciones de una forma más precisa y activa. En los últimos años, ha surgido una nueva interdiscipina compuesta por Neurociencia y Marketing, con cuyas técnicas los investigadores pueden evaluar la eficacia de la estrategia de marketing a través del análisis del procesamiento cognitivo del consumidor. Sin embargo, la aparición del Neuromarketing ha provocado algunas preocupaciones y críticas en relación con la intrusión de la medición fisiológica en el estudio del comportamiento del consumidor. Numerosos investigadores han puesto de manifiesto que el uso de algunas de las herramientas de Neuromarketing, como facial coding o fMRI,pueden causar una pérdida de privacidad personal e, incluso, conducir a la discriminación, estigmatización y coerción de individuos o grupos específicos. De ahí, ha surgido la discusión sobre la ética y la responsabilidad en experimentos de Neuromarketing. A partir de una revisión de la literatura científica, este estudio pretende discutir sobre los problemas éticos en los estudios de Neuromarketing, teniendo en cuenta sus surgimientos, desarrollos y futuros. Este artículo proporciona a los investigadores de neuromarketing una referencia en los dilemas éticos del Neuromarketing y también sienta las bases para la investigación de seguimiento del autor.

Esta ponencia con carácter de un ensayo teórico pretende ampliar los horizontes del neuromarketing hacia causas sociales, pero sustentado con la recopilación de algunos ejemplos de estudios prácticos de investigadores del neuromarketing, así como de las causas de las adicciones y su afectación en el cerebro, debido a las substancias adictivas. Las investigaciones han logrado grandes avances en la etiología y dinámica de las adicciones, por lo que se propone en esta ponencia que el neuromarketing puede aplicarse también en las campañas para prevenir las adicciones en la sociedad, principalmente entre adolescentes. Es proponer a la comunidad académica y científica la creación de una nueva rama inexistente actualmente como área específica de investigación a futuro denominada neuromarketing social (o de causas sociales) que combine las investigaciones en mercadotecnia con los hallazgos en las neurociencias. A pesar de este conocimiento sobre la reacción cerebral en las adicciones que han estudiado los neurocientíficos, falta todavía que se conecte este conocimiento de las reacciones adictivas y emocionales con campañas preventivas que puedan ayudar a disminuir estos problemas antes de volverse una adicción. La aplicación de las herramientas de medición de las neurociencias puede mejorar los resultados de las campañas preventivas. En este sentido es un llamado abierto a profesores, alumnos e investigadores de instituciones académicas para realizar más investigaciones prácticas para acumular experiencias nuevas que permitan crecer los casos prácticos de solución de problemas del neuromarketing social.

This study investigates the prospects of using electroencephalography (EEG) in tourism and hospitality research. It first discusses the concept and importance of EEG. Then, it systematically reviews articles that have used EEG to measure psychophysiological responses in business and management. The review mainly discusses EEG themes/theories/concepts and EEG methods and indices. Based on the review, this study analyses main challenges of applying EEG and suggests solutions to solve them. It finally proposes some future applications of EEG in tourism and hospitality. This study is one of the first to offer a better understanding of the literature, analysis methods, and theories/concepts associated with EEG, informing future EEG applications in tourism and hospitality research.

Neurocomputing studies on consumer attitudes have recently made a significant contribution to branding psychology. This study investigates consumer decisions for a branded stimulus using advanced machine learning algorithms. Electroencephalogram (EEG) signals were recorded during experiments in which ten branded and ten unbranded smartphones were shown to the subjects as stimuli. Then, EEG signals were classified using a methodological approximation consisting of four stages: pre-processing, feature extraction, channel selection, and classification. This is the first time a four-stage methodology has been applied in a neuromarketing study. The analysis study employed autoregressive (AR), principal component analysis (PCA), and piecewise constant modeling (PCM) in the feature extraction stage; artificial bee colony (ABC) and independent component analysis (ICA) in the channel selection stage; and artificial neural network (ANN) and support vector machine (SVM) in the classification stage. By comparing the successes of the methods in each stage, the methodological combination that gives the best classification performance was determined. According to the results, 72% accuracy was obtained in the average classification and an 85% accuracy on an individual basis. In the classification that achieved the best success, PCA in feature extraction, ABC in channel selection, and ANN in classification were used. In addition, the AF3-F7 (frontal brain regions) channels were observed to be the best-decomposed channel pair for different classes. The results also showed that stimulation within the brain for a branded product occurred at about 200 ms after the stimulus onset.

Aim. The presented study aims to determine the reaction of Chinese consumers to the use of e-commerce and neuromarketing tools during the coronavirus pandemic and to develop guidelines for e-commerce companies regarding the use of neuromarketing tools in the post-pandemic period.Tasks. The authors assess the awareness and attitude of respondents as consumers (individuals) regarding e-commerce tools in the People’s Republic of China (PRC); assess the attitude of respondents as consumers (individuals) to neuromarketing tools in e-commerce in the PRC during the pandemic; develop guidelines for improving the neuromarketing methodology in the PRC in the post-pandemic period.Methods. The authors test several hypotheses using statistical analysis. The hypotheses are tested in practice on the basis of a survey (using handouts and online questionnaires) of individuals. The attitude of Chinese citizens to the use of e-commerce tools is examined. The respondents are asked questions with one answer, multiple answers, and Likert scale questions. Data is processed using IBM SPSS Statistics 26 software and statistical methods, such as frequency analysis, contrast of means, and a number of others.Results. The opinion of Chinese consumers on the practice of using neurotechnologies in e-commerce is comprehensively assessed. The study analyzes the awareness of Chinese consumers regarding neurotechnologies and their own consumer behavior, showing their attitude to the use of neurotechnologies in e-commerce in the context of the pandemic.Conclusions. First, the COVID-19 pandemic has not significantly affected the overall income and spending of Chinese citizens. Only one-third of the Chinese population has increased their use of e-commerce platforms to make online purchases. Second, the pandemic has changed the consumption patterns of the Chinese population, making them more open to online shopping. Third, the average time of browsing products and making purchasing decisions on e-commerce platforms for Chinese residents did not change significantly during the pandemic. Fourth, while some Chinese consumers had a negative experience using e-commerce platforms during the pandemic, they used them more often than usual and will make more online purchases in the post-pandemic era. Fifth, when making online purchases, Chinese consumers always pay attention primarily to the quality and price of goods rather than other factors.

In a pandemic, the banking sector of the Russian Federation faced many economic problems. One of these challenges is customer acquisition and retention. In addition to the traditional "marketing mix", tools and methods of innovative marketing are becoming more widespread, which include neuromarketing and Internet marketing. Neuromarketing methods have shown their effectiveness on foreign platforms, therefore, considering their use in the financial sector of Russia is a new non-standard way to attract new customers and increase loyalty of old customers. In this article, the author provides information on the methods of neuromarketing used, which include: electrical activity of the skin; monitoring the cardiovascular system; eye-tracking; functional magnetic resonance imaging (MRI); electroencephalography (EEG); electromyography (fEMG); analysis of human mimic reactions. Based on the well-known emotional triggers of a person (sight, smell, touch, hearing, taste), marketing tools are presented that are used in the banking sector of the Russian Federation. The analysis of neuromarketing tools in the TOP-5 banks in terms of profit for 2020 was also carried out. Recommendations on the use of new tools are offered and conclusions are drawn about the situation with the use of neuromarketing in the Russian Federation.

Until now, neuromarketing studies have usually been aimed at assessing the predictive value of psychophysiological measures gathered while watching a marketing message related to a particular product. This study is the first attempt to verify the possibility of predicting familiar and unfamiliar brand purchases based on psychophysiological reactions to a retailer television advertisement measured by EEG, EDA and eye-tracking. The number of private label products chosen later served to assess the binary dependent variable. A logistic regression model (with a prediction rate of 61.2%) was applied to determine which psychophysiological variables explained the largest part of the variance of a final purchase decision. The results show that among various measures, only the electrodermal peaks per second were significant in predicting further purchase decisions. The decision to buy was also influenced by brand familiarity. The article concludes that EDA is an unobtrusive measure of emotion-related anticipation of significant outcomes, particularly for dynamic stimuli, as related to decision-making.

In this study, a liking estimation system based on electroencephalogram (EEG) signals is developed for neuromarketing applications. The determination of the degree of appreciation of a product by consumers has become an important research topic using machine learning methods. Biological data is recorded while viewing product pictures or videos, then processed by signal processing methods. In this study, 32 channel EEG signals are recorded from subjects who watched two different car advertisement videos and the liking status is determined. After watching the advertisement videos, the participants were asked to vote for the rating of the different images (front view, dashboard, side view, rear view, taillight, logo and grille) of the products. The signals corresponding to these different video regions from the EEG recordings were segmented and analyzed by the Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD). The statistical features were extracted from Intrinsic Mode Functions (IMF) and the liking status classifications were performed. The classification performance of EMD- and EEMD-based methods are 93.4% and 97.8% respectively on Brand1, and 93.5% and 97.4% respectively on Brand2. In addition, the classification accuracy on both brands combined are 85.1% and 85.7% respectively. The promising results obtained using Support Vector Machines (SVM) show that the proposed EEG-based method may be used in neuromarketing studies.

Information technology and its implications have shown significant developments in the last decades. The internet revolution and digital marketing have created a shrinking force on mass media advertising. They have formed the backbone of personalisation, marketing automation, neuromarketing, viral marketing, voice recognition, and conversion optimisation, and thus, Artificial Intelligence (AI) has risen as the phenomenon in marketing activities. Theoretical analysis of relevant researches on AI tools and future trends, presentation of conceptual framework and methodology design, and presentation of the research findings are the objectives of the research. This study has potential limitations such as the data collection process and access to the relevant literature. AI for marketing has already become a significant part of today’s competitive world, which utilising the marketing opportunities to obtain business goals and create breakthrough using AI. Hence, this paper aims to illustrate the theoretical review on the nexus between AI and marketing, which would lead to understanding the future scope of AI and its penetration in marketing activities.

Tourism as a social phenomenon has attracted the attention of marketers throughout all stages of its development. Successful cooperation between tourism entities and customers is based on communication. The persuasive power of advertising language is very much experienced today. The same happens in relation to tourism marketing materials. In fact, in order to attract the attention of the viewers, the travel companies choose various signs to express their notion of the brand. Hence, there exist different approaches in tourism marketing to attract and convince potential tourists to book a tourism product. The present article elucidates and discusses important aspects in relation to the language of tourism and the ways of its analysis for detecting persuasive techniques that are used to allure potential tourists. In this regard, the speech impact on travel advertising is realized by convincing a potential customer of the need for service / product. When advertising a travel product, the advertiser influences the consumer, attracting various effective means to intensify his desire to purchase travel services (travel product). The paper reviews the elements of persuasive tourism marketing such as structured communication, storytelling, copywriting, neuromarketing; Cialdini’ (2001) persuasion techniques to influence people, namely, reciprocation, commitment and consistency, social proof, liking, authority, and scarcity. The article also highlights gender-targeting factors as important components in selecting an appropriate persuasive strategy when designing tourism promotional materials. The result section provides the real examples of deployment of the mentioned strategies in influencing the audience by the websites of “Karpaty” and “Solva” resorts. All these techniques form a theoretical framework for researches on persuasiveness and are worth attention as they play a main role in promotion of any kind. The data collection of this study will provide updated information in relation to rhetoric of tourism.

Considerable research has been conducted globally showing how study results are substantially conditional to the interest and productivity of a learner in the studies and the emotions and stress the learner experiences. Scholars emphasize that learning should be pleasing, enticing, and emotionally positive leading to increased effectiveness of the studying. Tests were conducted regarding the effectiveness of the MSc Property management studies process among students. Development of the ARTSY Model involved five iterative phases over the course of the research. ARTSY Model, intelligent and physiological technologies that had helped as the foundation for creating the Affect-based, Multimodal, Video Tutoring System for a Neuromarketing (ARTSY) were applied for this research. The research motivation and one of the main purposes are to increase students learning productivity, interest, emotions and decrease stress levels. According to this research motivation, ARTSY was developed. Upon comparison with the most advanced, existing affective tutoring systems, two innovative elements are distinguishing ARTSY. First, automatic means to develop and select the most effective variants from thousands of textual and video learning material alternatives by considering learner interest, productivity and stress levels. Secondly, exams or tests are unnecessary for assessing student knowledge levels by employing the newly developed Calculating a Student’s Self-assessment Grade. ARTSY’s future betterments are expected to achieve comprehensive and dependable, real-time information, not only about student needs but also about existing opportunities. A consequent outcome could be greater flexibility in the study process for students. This paper composed of Introduction (Section 1), Research background (Section 2), ARTSY Model description (Section 3) and the Construction of ARTSY (Section 4). The conclusions and notes for future study provide the ending to this article in Section 5.

Neuroscience Research Notes (ISSN: 2576-828X) was established in 2018 by a group of neuroscientists out of frustration and struggle to pay off any article processing charges for open access publication. Ever since its establishment, the journal has been steered to cater to high quality, short research and technical reports in all aspects of the nervous system. The journal emphasises hypothesis formation, research methodology, data interpretation and conclusion derived from both positive and negative findings, orphaned studies or neglected observations of related research fields. To date, the journal has received 66 submissions, with a 27% rejection rate. The average number of days for an editor to reach the first decision to accept any manuscript for further peer-reviewing is 5-day. However, it takes about 80-98 days (3 months) from submitting an article to final publication or rejection. The timeline of publishing with Neuroscience Research Notes is considered competitive and reasonable in fulfilling authors’ interest in having their research published as soon as possible while safeguarding the sanctity of the scientific peer-reviewing process.

This study introduces and provides evidence of an Evolutionarily Stable Signalling (ESS) System in the buyer-seller context through three experiments. An ESS system is one where a signaller (in thi...

La investigación “Medición en base al neuromarketing del engagement en la comunicación publicitaria online en las universidades privadas de la Ciudad de Huancayo”, buscó determinar el nivel de engagement en la comunicación publicitaria online en las universidades privadas de la Ciudad de Huancayo. La metodología empleada es de tipo básica teórica, con nivel descriptivo correlacional, se utilizó el método científico y con un diseño transeccional descriptivo simple. El nivel de engagement varía de forma significativa, en la publicidad online que las Universidades implementan, la Universidad Continental es la que alcanza el mayor nivel de engagement y la UPLA es la que alcanza el nivel más bajo de engagement. Las imágenes publicitarias son clave cuando de generar engagement positivo se trata, indudablemente a través del contenido visual se pueden establecer relaciones emocionales, despertar la curiosidad del cliente es necesario. En el caso de las Universidades Privada de en Huancayo solo algunas lo están logrando con algunos aspectos como experiencias, actividades, eventos y un lenguaje amigable.

Traditional marketing strategies are now no longer seen as effective in communicating with today’s sophisticated groups. Today, companies employ knowledge from disciplines other than marketing – su...

Subject. This article discusses the marketing communication tools based on the application of neuromarketing technology that help brands create products that meet the needs of customers as much as possible. Objectives. The article aims to define consumers' perception of dynamic advertising information content in the food category. Methods. For the study, we used a comparative analysis, synthesis, dialectical methods, as well as a systems approach to data assessment, and marketing questionnaires. Results. The article describes the basic methods and technologies used in neuromarketing, which help evaluate such unconscious reactions as a level of attention and emotional investment, activation of memory. The article also presents the results of an empirical study of respondents' perception of nowaday commercials. Conclusions. The use of traditional marketing methods does not always yield the expected results. The use of neuromarketing tools has certain prospects in measuring the conscious and unconscious response of consumers during the product development and promotion phases.

The article aimed at researching the benefits of eye-tracking technology in terms of the market research, product promotion and pricing strategy. The important potentials of using eye tracking technology in the practical marketing activities such as branding, segmentation, product development, pricing solutions, placement strategies, advertising solutions and social marketing are examined. The term «eye tracking» as it is used in neuromarketing means assessing the direction of the user’s gaze. The main area of its commercial application was the study of the perception of the composition of newspaper strips and magazines, design and packaging of products. With the spread of the Internet and the entry of companies into the network space, eye tracking has received a new round of development associated with the study of the perception of websites. Tracking the direction of the consumer’s gaze in the market research can give an idea of the consumers’ habits, even if those consumers do not know that they are being watched. The research using eye tracking technology can help developing new products, improving consumer segmentation, and choosing a good pricing policy. It is displayed that there is a wide range of possibilities of using eye tracking methods in both neuromarketing and market research. A conclusion is drawn that neuromarketing and its eye tracking technology are becoming increasingly popular both in academia and in the business world.

The analysis of the influence of neuromarketing as a tool for marketing activities in the Internet environment, to increase the loyalty of tourists to tourism enterprises in the context of the service sector. The channels of percep-tion on which neuromarketing affects are analyzed and structured. Analyze different approaches to the definition of the essence of neuromarketing on which prompted the author's vision of the related concepts. The article considers the concept of neuromarketing and its interpretation. Аn overview of neuromarketing tools, their advantages and disadvantages, and the possible scope of their application is given. The main problems of using neuromarketing tools are also discussed. The research points to the usefulness of neuromarketing at positioning the destination brand. Problems and prospects of using neuromarketing in the Internet space for promoting tourist services are con-sidered. Additionally, the complexity of neuromarketing research perception means that it is inadvisable to use the obtained data in isolation. It is proved that the perception of information on the Internet changes every year, as evidenced, for example, the so-called "banner blindness", new methods and communication channels are needed to support the loyalty of existing customers and attract new ones. The areas where used neuromarketing: strategic instrumentary, neuromarketing research are considered and systematized. In addition, it has been proven that information that is provided without visual support is usually not perceived as effective. It has been proved that neuromarketing in symbiosis with traditional marketing methods and tools provides an opportunity to solve several the above problems. The appliance of neuromarketing tourism market research thus assumes a novel conceptual approach, one that quite differs from the standard. Keywords: neuromarketing, strategic marketing, internet marketing, marketing in tourism.

The article discusses the global growth in interest in neuromarketing from the first official neuromarketing study to the present day. A brief list of neuromarketing definitions in chronological sequence is given and key changes in the definition are traced. A detailed analysis of indicators of growing interest in neuromarketing technologies as indicators of potential advantages in terms of increasing publication activity, growing interest in using neuromarketing technologies in business, as well as increasing popularity of the direction is made. The review of works devoted to bibliographic analysis, meta-analysis of works in the field of neuromarketing as a key indicator of growth in demand for the direction is given. The main “highlights” of publishing activity are considered, as well as dynamic growth of publications according to Google Scholar data. Awareness and attitude of the general public and business to neurotechnologies and neuromarketing as well as their readiness to use these technologies are shown in dynamics. The process of growing interest in neuromarketing from business communities is highlighted. The main force of consolidation of neuromarketing advantages is revealed. The reasoning of the research community in favor of using neuromarketing techniques is shown. The main strategies of companies’ work to bring successful “new” product to the market with statistical data are listed. The main advantages of technologies potentially increasing the chances of success of a new product are listed. We speak about neurotechnologies as a tool for obtaining valuable marketing information in the food industry: from the stage of development to the stage of product implementation. The main areas of application of neuromarketing technologies in business are listed. The features of application of neurotechnologies in the food industry are shown. Some researches in the field of sensory marketing which testify to presence of indirect influence of sensory stimuli on perception of a product are designated. The main key advantages of neuromarketing technologies, which are consistent with the latest achievements in neuromarketing, as well as those advantages which are of discussion nature, are marked out. The advantages identified relate to both the data collection technology and its processing, which includes the potential of the technology in mass application.

This research project has the goal to verify whether the application of neuromarketing techniques, such as implicit association test (IAT) techniques and emotional facial expressions analyses may contribute to the assessment of user experience (UX) during and after website navigation. These techniques have been widely and positively applied in assessing customer experience (CX); however, little is known about their simultaneous application in the field of UX. As a specific context, the experience raised by different websites from two well-known automotive brands was compared. About 160 Italian university students were enrolled in an online experimental study. Participants performed a Brand Association Reaction Time Test (BARTT) version of the IAT where the two brands were compared according to different semantic dimensions already used in the automotive field. After completing the BARTT test, the participants navigated the target website: 80 participants navigated the first brand website, while the other half navigated the second brand website (between-subject design). During the first 3 min of website navigation, emotional facial expressions were recorded. The participants were asked to freely navigate the website home page, look for a car model and its characteristics and price, use the customising tool, and in the end, look for assistance. After the website navigation, all the participants performed, a second time, the BARTT version of the IAT, where the two brands were compared again, this time to assess whether the website navigation may impact the Implicit Associations previously detected. A traditional evaluation of the two websites was carried on by means of the classic heuristic evaluation. Findings from this study show, first of all, the significant results provided by neuromarketing techniques in the field of UX, as IAT can provide a positive application for assessing UX played by brand websites, thanks to the comparison of eventual changes in time reaction between the test performed before and after website navigation exposure. Secondly, results from emotional facial expression analyses during the navigation of both brand websites showed significant differences between the two brands, allowing the researchers to predict the emotional impact raised by each website. Finally, the positive correlation with heuristic evaluation shows that neuromarketing can be successfully applied in UX.

The new era of digitalized knowledge and information technology (IT) has improved efficiency in all medical fields, and digital health solutions are becoming the norm. There has also been an upsurge in utilizing digital solutions during the COVID-19 pandemic to address the unmet mental healthcare needs, especially for those unable to afford in-person office-based therapy sessions or those living in remote rural areas with limited access to mental healthcare providers. Despite these benefits, there are significant concerns regarding the widespread use of such technologies in the healthcare system. A few of those concerns are a potential breach in the patients' privacy, confidentiality, and the agency of patients being at risk of getting used for marketing or data harnessing purposes. Digital phenotyping aims to detect and categorize an individual's behavior, activities, interests, and psychological features to properly customize future communications or mental care for that individual. Neuromarketing seeks to investigate an individual's neuronal response(s) (cortical and subcortical autonomic) characteristics and uses this data to direct the person into purchasing merchandise of interest, or shaping individual's opinion in consumer, social or political decision making, etc. This commentary's primary concern is the intersection of these two concepts that would be an inevitable threat, more so, in the post-COVID era when disparities would be exaggerated globally. We also addressed the potential “dark web” applications in this intersection, worsening the crisis. We intend to raise attention toward this new threat, as the impacts might be more damming in low-income settings or/with vulnerable populations. Legal, health ethics, and government regulatory processes looking at broader impacts of digital marketing need to be in place.

In e-commerce settings, shoppers can navigate to product-specific pages on which they are asked to make yes-or-no decisions about buying a particular item. Beyond that target, there are often other products displayed on the page, such as those suggested by the retailers’ recommendation systems, that can influence consumers’ buying behavior. We propose that display items that come from the same category as the target product (matched) may enhance target purchase by increasing the attractiveness of the presented opportunity. Contrasting this, mismatched display items may reduce purchase by raising awareness of opportunity costs. Eye-tracking was used to explore this framework by examining how different types of displays influenced visual attention. Although target purchase rates were higher for products with matched vs. mismatched displays, there was no difference in fixation time for the target images. However, participants attended to mismatched display items for more time than they did for matched ones consistent with the hypothesized processes. In addition, increases in display attractiveness increased target purchase, but only for matched items, in line with supporting the target category. Given the importance of relative attention and information in determining the impact of display items, we replicated the overall purchase effect across varying amounts of available display information in a second behavioral study. This demonstration of robustness supports the translational relevance of these findings for application in industry.

Neuroforecasting predicts population-wide choices based on neural data of individuals and can be used, for example, in neuromarketing to estimate campaign successes. To deliver true value, the brain activity metrics should deliver predictive value above and beyond traditional stated preferences. Evidence from movie trailer research has proposed neural synchrony, which compares the similarity of brain responses across participants and has shown to be a promising tool in neuroforecasting for movie popularity. The music industry might also benefit from these increasingly accurate success predictors, but only one study has been forecasting music popularity, using functional magnetic resonance imaging measures. Current research validates the strength of neural synchrony as a predictive measure for popularity of music, making use of electroencephalogram to capture moment-to-moment neural similarity between respondents while they listen to music. Neural synchrony is demonstrated to be a significant predictor for public appreciation on Spotify 3 weeks and 10 months after the release of the albums, especially when combined with the release of a single. On an individual level, other brain measures were shown to relate to individual subjective likeability ratings, including Frontal Alpha Asymmetry and engagement when combined with the factors artist and single release. Our results show the predictive value of brain activity measures outperforms stated preferences. Especially, neural synchrony carries high predictive value for the popularity on Spotify, providing the music industry with an essential asset for efficient decision making and investments, in addition to other practical implications that include neuromarketing and advertising industries.

Real-time gaze tracking provides crucial input to psychophysics studies and neuromarketing applications. Many of the modern eye-tracking solutions are expensive mainly due to the high-end processing hardware specialized for processing infrared-camera pictures. Here, we introduce a deep learning-based approach which uses the video frames of low-cost web cameras. Using DeepLabCut (DLC), an open-source toolbox for extracting points of interest from videos, we obtained facial landmarks critical to gaze location and estimated the point of gaze on a computer screen via a shallow neural network. Tested for three extreme poses, this architecture reached a median error of about one degree of visual angle. Our results contribute to the growing field of deep-learning approaches to eye-tracking, laying the foundation for further investigation by researchers in psychophysics or neuromarketing.

Los patrones normales de movimiento ocular de lectura tienen tres componentes principales: movimientos sacádicos, que mueven los ojos de una palabra a otra; movimientos sacádicos, que devuelven los ojos al comienzo de la siguiente línea; y pausas de fijación entre cada movimiento sacádico para el procesamiento de la información. Las propuestas de patrones oculares en imágenes estáticas sirven para corroborar el comportamiento de orden de visualización o lectura. En este trabajo se ha verificado, mediante biometría de neuromarketing, el patrón de respuesta a un estímulo estático, basado en un texto con cambios de tamaño de letra y ubicación, el cual prevé el patrón de fijación de los usuarios. La biometría empleada fue eye tracking, obteniendo datos de visualización, mapas de calor y mapas de fijación que verifican el orden seguido por la mayoría de los usuarios. Con esta técnica pasiva se pretendía obtener los patrones mentales de lectura, estableciendo las áreas de interés previamente, a través de la aplicación informática del eye tracker. El resultado confirma que el patrón de lectura no se corresponde a las indicaciones del texto en la imagen estática, descartando la propuesta del estímulo y descubriendo que el ojo lee en un determinado orden, según la cultura de aprendizaje. Normal reading eye movement patterns have three main components: saccades that move the eyes from one word to another, saccades that return the eyes to the beginning of the next line, and fixation pauses between each saccade for word processing. information. The proposals for ocular patterns in static images serve to corroborate the behaviour of the order of viewing or reading. In this work, the response pattern to a static stimulus has been verified using neuromarketing biometrics, based on a text with changes in font size and location, which anticipates the users’ fixation pattern. The biometrics used was eye tracking, obtaining visualization data, heat maps and fixation maps that verify the order followed by the majority of users. This passive technique was intended to obtain mental reading patterns, establishing areas of interest previously, through the eye tracker computer application. The result confirms that the reading pattern does not correspond to the indications of the text in the static image, discarding the stimulus proposal and discovering that the eye reads in a certain order, according to the learning culture.

Culture strategy is very important for transnational brand marketing. Functional near-infrared spectroscopy (fNIRS) is a promising brain imaging modality for neuromarketing research. In the present study, we used fNIRS to explore the neural correlates of consumers’ purchase decision on different cross-culture marketing strategies. Forty Chinese participants watched transnational brands and products advertised with photographs of the brands’ original culture (the original culture advertisements) and advertised with photographs of Chinese culture (the mixed culture advertisements), respectively. The behavioral results showed that the female participants showed significantly higher purchase rate when watching the original culture advertisements than the mixed culture advertisements, whereas the male participants did not show significant preference between these two types. The fNIRS results further revealed that for the female participants, watching mixed culture advertisements evoked significant positive activation in the left dorsolateral prefrontal cortex and negative activation in the medial prefrontal cortex, which was not found in the male participants. These findings suggest possible cognitive and emotional differences between men and women in purchase decision making toward different cross-culture marketing strategy. The present study also demonstrates the great potential of fNIRS in neuromarketing research.

Brain–computer interfaces (BCIs) establish communication between a human brain and a computer or external devices by translating the electroencephalography (EEG) signal into computer commands. After stimulating a sensory organ, a positive deflection of the EEG signal between 250 and 700ms can be measured. This signal component of the event-related potential (ERP) is called “P300.” Numerous studies have provided evidence that the P300 amplitude and latency are linked to sensory perception, engagement, and cognition. Combining the advances in technology, classification methods, and signal processing, we developed a novel image ranking system called the Unicorn Blondy Check. In this study, the application was tested on 21 subjects using three different visual oddball paradigms. Two consisted of female faces and gray-scale images, while the third test paradigm consisted of familiar and unfamiliar faces. The images were displayed for a duration of 150ms in a randomized order. The system was trained using 50 trials and tested with 30 trials. The EEG data were acquired using the Unicorn Hybrid Black eight-channel BCI system. These synchronized recordings were analyzed, and the achieved classification accuracies were calculated. The EEG signal was averaged over all participants and for every paradigm separately. Analysis of the EEG data revealed a significant shift in the P300 latency dependent on the paradigm and decreased amplitude for a lower target to non-target ratio. The image ranking application achieved a mean accuracy of 100 and 95.5% for ranking female faces above gray-scale images with ratios of 1:11 and 5:11, respectively. In the case of four familiar faces to 24 unfamiliar faces, 86.4% was reached. The obtained results illustrate this novel system’s functionality due to accuracies above chance levels for all subjects.

The present study investigates the applicability of deep learning methods in EEG neuromarketing prediction tasks, compared to traditional machine learning approaches. Neuroscientific methods have expanded research capabilities in marketing and created new insights into consumer behavior and decision making processes. Both machine learning and deep learning approaches can be employed to predict relevant consumer preference from brain activity. The former requires extensive signal processing and feature engineering for classification whereas the later relies on raw brain signals and thus avoids time-consuming preprocessing. In this paper, the performance of a machine learning model comprising an ensemble of algorithms was compared to the performance of a convolutional neural network (CNN) on two independently collected EEG datasets, one concerning product choices and the other movie ratings. While both models showed poor performance for prediction of product choices, the convolutional neural network proved more accurate in the prediction of movie ratings. This provides evidence for the superiority of deep learning algorithms in certain neuromarketing prediction tasks. We discuss the limitations and future application opportunities.

Purpose The purpose of this paper is the better understanding of the increasing relation between big data 2.0 and neuromarketing, particularly to influence election outcomes, along with a special aim to discuss some raised doubts about Trump’s presidential campaign 2016 and its ability to hijack American political consumers’ minds, and to direct their votes. Design/methodology/approach This paper combines deductive/inductive methodology to define the term of political neuromarketing 2.0 through a brief literature review of related concepts of big data 2.0, virtual identity and neuromarketing. It then applies a single qualitative case study by presenting the history and causes of online voter microtargeting in the USA, and analyzing the political neuromarketing 2.0 mechanisms adopted by Trump’s political campaign team in the 2016 presidential election. Findings Based on Trump’s political marketing mechanisms analysis, the paper believes that big data 2.0 and neuromarketing techniques played an unusual role in reading political consumers’ minds and helping the controversial candidate to meet one of the most unexpected victories in the presidential elections. Nevertheless, this paper argues that the ethics of using political neuromarketing 2.0 to sell candidates and its negative impacts on the quality of democracy are and will continue to be a subject of ongoing debates. Originality/value The marriage of big data 2.0 and political neuromarketing is a new interdisciplinary field of inquiry. This paper provides a useful introduction and further explanations for why and how Trump’s campaign defied initial loss predictions and attained victory during this election.

The article is based on the results of the 7th International Scientific and Practical Conference on Economics “The Market Economy Phenomenon: From the Origins into Our Days” held from March 27 to March 31, 2019 in the cities of Sochi and Sukhumi. The theoretical approaches of domestic and foreign researchers to understanding the market economy phenomenon, the specifics of its financial and credit sphere functioning in the context of the digital economy were generalized. The problems of the monetary economy in terms of the sanction confrontation were outlined. The authors analyzed and evaluated the processes and the phenomena observed in the post-Soviet economic space related to the transplantation of market economy mechanisms into the system of social reproductive relations, including its financial component based on their digitalization. The dialectic approach, system analysis, methods of economic and statistical and interdisciplinary analytical tools were used. The article revealed the key components of the market economy phenomenon appearing in the post-Soviet economic space and having a direct impact on the social reproduction results. The relationship was shown between the transformation of the evolutionary and methodological content of the money economy, its institutional and behavioral paradigm, the digitalization of the financial segment of the economic space with the scale of innovation, the penetration of cognitive psychology and neurophysiology into financial and credit relations, and their technological re-equipment. The results of the influence of instability factors on the budget and monetary sphere were presented. The authors described complex interdependencies of the processes and phenomena within the framework of the market economy phenomenon appearing in the post-Soviet economic space. The triune structure of the modern market doctrine was disclosed including psychological and behavioral, institutional and functional and reproduction and product aspects. The authors showed the transformational dynamics of the financial and credit sphere of modern society. Its specific features are: the increasingly important role of innovation, outsourcing, revising pricing methods, digitalization of business processes, penetration into managing neuromarketing technologies, and virtualization of the financial sector of the economy.

Through the present article neuromarketing as a research method is discussed, starting from definitions, to instruments available, ending with an analysis of the ethical issue of the field. The novel ty of the study is that perceptions and experiences of neuromarketing practitioners are presented, therefore contributing to the knowledge creation regarding this type of marketing research.

Aim. The presented study aims to gauge the reactions of Russian and Chinese consumers to the use of neuromaketing tools. In the course of the study, several hypotheses are tested using statistical analysis.Tasks. The authors assess the awareness of the respondents in the field of interest and their attitude as consumers (individuals) to neuromarketing and the use of neurotechnology in Russia and China. Methods. The hypotheses are tested in practice using a questionnaire survey of the respondents (by means of a handout questionnaire or an online questionnaire). The assessment of the attitude to the use of neuromarketing tools by the citizens of the Russian Federation and China is examined. The respondents are asked questions with one answer, multiple answers, and Likert scale questions. Data are processed in IBM SPSS Statistics 24 using such statistical methods as frequency analysis, contrast of means, etc.Results. The opinion of Russian and Chinese consumers on the use of neurotechnology for commercial purposes is comprehensively assessed. The study analyzes the issues of the awareness of Russian and Chinese citizens about neurotechnology, their own consumer behavior, and their attitude to the use of neurotechnology. Consumer opinion is examined to determine the risk of public discontent and prejudice against the implementation of neurotechnology.Conclusions. Both Russia and China are facing potential threats to the development of neurotechnology from public opinion. The risk of a statutory ban on neurotechnology due to public discontent and low perception of the ethical aspect of this tool by consumers in Russia and China is vastly overstated by contemporary researchers and media. Consumers are actually rather tolerant of the examined tool and show no signs of discontent or fear. The long-term relevance of the obtained data isobvious.

Neuromarketing as research method contrbutes to understanding consumer behavior a step further than traditional marketing research. The aim of the current study is to explore the usability and cognitive understanding of banking services webpages. In this regard, the theoretical part of the article reviews the relevant literature related to neuromarketing as research method and the use of eye-tracker as research technique. Further on, a two-step research design was developed for studying the consumers’ attention and memory during and after viewing two Romanian banking services websites. The results showed that the way information is structured and presented on the webpages influence their usabiliy and cognitive understanding.

Purpose The purpose of this paper is to determine the auditory-sensory characteristics of the digital pop music that is particularly successful on the YouTube website by measuring young listeners’ brain responses to highly successful pop music noninvasively. Design/methodology/approach The authors conducted a functional near-infrared spectroscopy (fNIRS) experiment with 56 young adults (23 females; mean age 24 years) with normal vision and hearing and no record of neurological disease. The authors calculated total blood flow (TBF) and hemodynamic randomness and examined their relationships with online popularity. Findings The authors found that TBF to the right medial prefrontal cortex increased more when the young adults heard music that presented acoustic stimulation well above previously defined optimal sensory level. The hemodynamic randomness decreased significantly when the participants listened to music that provided near- or above-OSL stimulation. Research limitations/implications Online popularity, recorded as the number of daily hits, was significantly positively related with the TBF and negatively related with hemodynamic randomness. Practical implications These findings suggest that a new media marketing strategy may be required that can provide a sufficient level of sensory stimulation to Millennials in order to increase their engagements in various use cases including entertainment, advertising and retail environments. Social implications Digital technology has so drastically reduced the costs of sharing and disseminating information, including music, that consumers can now easily use digital platforms to access a wide selection of music at minimal cost. The structure of the current music market reflects the decentralized nature of the online distribution network such that artists from all over the world now have equal access to billions of members of the global music audience. Originality/value This study confirms the importance of understanding target customer’s sensory experiences would grow in determining the success of digital contents and marketing.

The dual aim of this research is, firstly, to analyze the physiological and unconscious emotional response of consumers to a new technological product and, secondly, link this emotional response to consumer conscious verbal reports of positive and negative product perceptions. In order to do this, biometrics and self-reported measures of emotional response are combined. On the one hand, a neuromarketing experiment based on the facial recognition of emotions of 10 subjects, when physical attributes and economic information of a technological product are exposed, shows the prevalence of the ambivalent emotion of surprise. On the other hand, a nethnographic qualitative approach of sentiment analysis of 67-user online comments characterise the valence of this emotion as mainly negative in the case and context studied. Theoretical, practical and methodological contributions are anticipated from this paper. From a theoretical point of view this proposal contributes valuable information to the product design process, to an effective development of the marketing mix variables of price and promotion, and to a successful selection of the target market. From a practical point of view, the approach employed in the case study on the product Google Glass provides empirical evidence useful in the decision making process for this and other technological enterprises launching a new product. And from a methodological point of view, the usefulness of integrated neuromarketing-eWOM analysis could contribute to the proliferation of this tandem in marketing research.

The active introduction of online communications into the life of a modern person has significantly changed advertising content. The use of digital technologies, interactive systems, virtual assistants, self-advertisement, and motion design provided for more comprehensive research methods, fundamental scientific approaches, collaboration with exact natural sciences in the brand promotion system. Today, web consumer behavior patterns are studied and monitored by a unique system of neural networks. The issues of applying neural technologies in various human activities are becoming particularly relevant and, in a way, getting a new growth stage due to the active extension of artificial intelligence developments. Changes in the communication sphere and its digitalization are also links in this process. Modern researchers are not only interested in artificial intellectual platforms, but also in the possible development of human intelligence, the uniqueness of the mental activity, as well as the technologies that would allow one to see directly the entire activity process, visible responses of the human brain, and its neural connection. State-of-the-art artificial intelligence technologies and specially developed software for digital communications of the source and target groups on the web allow us to compare, correlate the body response to external stimuli with the processes in the neural network. The development of neural networks is the driving force for the communication sphere. Neural networks can analyze and correctly apply the data on target groups in the digital marketing communications system and produce over a thousand "product" solutions, which serve microsegments of target groups in a spot manner, can track the customer journey in all sales channels, and the algorithm will also choose where and when to place a message and how many times it should appear in the customer’s field of vision. Neural technologies come to the fore in marketing communications allowing one to identify the true (not filtered by consciousness) responses of a potential consumer to various marketing materials. Tools are needed to analyze a vast base of personal data, the volume of which is constantly growing and should be processed. Due to the digitalization of marketing communications activities, many functions of marketing experts are gradually moving into the function of the software implemented by neural network technologies. The fact that the target product began to be promoted in a more tailored and effective manner is linked with the digitalization of communications, the use of psychophysiological methods implemented in neuromarketing. This research studies digital forms of advertising and consumer responses to advertising-graphic content using a complex of traditional and neuromarketing techniques. The object of research is digital content of telecommunication brands.

There is an increasing demand within consumer-neuroscience (or neuromarketing) for objective neural measures to quantify consumers’ preferences and predict responses to marketing campaigns. However, the properties of EEG datasets raise various difficulties when performing predictions on them, such as the small size of data sets, high dimensionality, the need for elaborate feature extraction, intrinsic noise, and unpredictable between-subject variations. We aimed to overcome these limitations by combining unique techniques within a Deep Learning (DL) framework, while providing interpretable results for neuroscientific and decision-making insight. In this study, we developed a DL model to predict subject-specific preferences based on their EEG data. In each trial, 213 subjects observed a product’s image, out of 72 possible products, and then reported how much they were willing to pay (WTP) for the product. The DL employed EEG recordings from product observation to predict the corresponding reported WTP values. Our results showed 75.09% accuracy in predicting high vs. low WTP, surpassing other models and a manual feature extraction approach. Meanwhile, network visualizations provided the predictive frequencies of neural activity and their scalp distributions, shedding light on the neural mechanism involved with evaluation. In conclusion, we show that DLNs may be the superior method to perform EEG-based predictions, to the benefit of decision-making researchers and marketing practitioners alike.