Neuroscience and Consumer Behavior: Where to Now?

Primacy Effect of Dynamic Multi-Sensory Covid ADV Influences Cognitive and Emotional EEG Responses

Advertising uses sounds and dynamic images to provide visual, auditory, and tactile experiences, and to make the audience feel like the protagonist. During COVID-19, companies modified their communication by including pandemic references, but without penalizing multisensorial advertising. This study investigated how dynamic and emotional COVID-19-related advertising affects consumer cognitive and emotional responses. Nineteen participants, divided into two groups, watched three COVID-19-related and three non-COVID-19-related advertisements in two different orders (Order 1: COVID-19 and non-COVID-19; Order 2: non-COVID-19 and COVID-19), while electrophysiological data were collected. EEG showed theta activation in frontal and temporo-central areas when comparing Order 2 to Order 1, interpreted as cognitive control over salient emotional stimuli. An increase in alpha activity in parieto-occipital area was found in Order 2 compared to Order 1, suggesting an index of cognitive engagement. Higher beta activity in frontal area was observed for COVID-19 stimuli in Order 1 compared to Order 2, which can be defined as an indicator of high cognitive impact. Order 1 showed a greater beta activation in parieto-occipital area for non-COVID-19 stimuli compared to Order 2, as an index of reaction for painful images. This work suggests that order of exposure, more than advertising content, affects electrophysiological consumer responses, leading to a primacy effect.

Emotional Effects in Object Recognition by the Visually Impaired People in Grocery Shopping

To date, neuroscientific literature on consumption patterns of specific categories of consumers, such as people with disability, is still scarce. This study explored the implicit emotional consumer experience of visually impaired (VI) consumers in-store. A group of VI and a control group explored three different product shelves and manipulated target products during a real supermarket shopping experience. Autonomic (SCL, skin conductance level; SCR, skin conductance response; HR, heart rate; PVA, pulse volume amplitude; BVP, blood volume pulse), behavioural and self-report data were collected in relation to three phases of the in-store shopping experience: (i) identification of a product (recognition accuracy, ACC, and reaction times, RTs); (ii) style of product purchase (predominant sense used for shelf exploration, store spatial representation, and ability to orientate themselves); (iii) consumers experience itself, underlying their emotional experience. In the VI group, higher levels of disorientation, difficulty in finding products, and repeating the route independently were discovered. ACC and RTs also varied by product type. VI also showed significantly higher PVA values compared to the control. For some specific categories (pasta category), PVA correlates negatively with time to recognition and positively with simplicity in finding products in the entire sample. In conclusion, VI emotional and cognitive experience of grocery shopping as stressful and frustrating and has a greater cognitive investment, which is mirrored by the activation of a larger autonomic response compared to the control group. Nevertheless, VI ability to search and recognise a specific product is not so different from people without visual impairment.

A Review of AI Cloud and Edge Sensors, Methods, and Applications for the Recognition of Emotional, Affective and Physiological States

Affective, emotional, and physiological states (AFFECT) detection and recognition by capturing human signals is a fast-growing area, which has been applied across numerous domains. The research aim is to review publications on how techniques that use brain and biometric sensors can be used for AFFECT recognition, consolidate the findings, provide a rationale for the current methods, compare the effectiveness of existing methods, and quantify how likely they are to address the issues/challenges in the field. In efforts to achieve the key goals of Society 5.0, Industry 5.0, and human-centered design better, the recognition of emotional, affective, and physiological states is progressively becoming an important matter and offers tremendous growth of knowledge and progress in these and other related fields. In this research, a review of AFFECT recognition brain and biometric sensors, methods, and applications was performed, based on Plutchik's wheel of emotions. Due to the immense variety of existing sensors and sensing systems, this study aimed to provide an analysis of the available sensors that can be used to define human AFFECT, and to classify them based on the type of sensing area and their efficiency in real implementations. Based on statistical and multiple criteria analysis across 169 nations, our outcomes introduce a connection between a nation's success, its number of Web of Science articles published, and its frequency of citation on AFFECT recognition. The principal conclusions present how this research contributes to the big picture in the field under analysis and explore forthcoming study trends.