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The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers one’s intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience.

The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently.

The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models.

Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverse’s experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverse’s economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust.

In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators.

The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models.

Neuromarketing is a marketing communication field that applies neuroscience and physiological research tools to study consumer behavior toward stimuli, viz., ads and brands. This study aims to assess research trends in the neuromarketing field on the most influential journals, authorships, countries, citations and co-occurrences. The Scopus database is used to analyze identified articles from 2013 to 2022 and for the eligible research articles, a “systematic methodological review” (SMR) on consumer behavior through neuromarketing approach was done. “Visualization of Science (VOS)” viewer and “Biblioshiny” by R-studio software have been used for mapping the keyword analysis, co-citation analysis and author occurrence analysis. It was further found that of the top 10 academic institutions, the list is dominated by the six Asian institutions. It was further witnessed that journal “Physiology and Behavior” is trending as the most dedicated and emerging journals on neuromarketing and consumer behavior. Asian nations such as Bangladesh, China, India, Indonesia, etc., are turning out to be an emerging collaborators and publishers in this niche area of research, thereby giving tough competition to most developed countries. The findings of the thematic mapping show that neuromarketing is itself a very novel and newest area of study and topics such as “human marketing,” “neuromarketing,” “consumer behavior” and “electroencephalography” are new dimensions that can be looked upon in future.

Tourism destination marketers use videos that incorporate storytelling and visual and audio components to evoke emotional arousal and memorability. This study aims to examine the increase in participants’ level of arousal and the degree of memorability after watching two different videos.

A quasi-experimental study was conducted with 45 participants who watched two destination promotional videos. One video used storytelling whereas the other used scenic images and music. The level of arousal was measured using both tonic and phasic electrodermal activity levels. The memorability of each video was measured after seven days by testing the recall accuracy.

Scenic imagery and music videos were associated with higher-than-average arousal levels, while storytelling videos generated larger-amplitude arousal peaks and a greater number of arousal-evoking events. After a week, the respondents recalled more events from the storytelling video than from the scenery and musical advertisements. This finding reveals that the treatment, storytelling and sensory stimuli in advertising moderate the impact of arousal peaks and memorability.

These results indicate that nonnarrative videos using only sceneries and music evoked a higher average level of arousal. However, memorability was associated with higher peak levels of arousal only in narrative storytelling. This is the first tourism study to report the effects of large arousal peaks on improved memorability in advertising.

The purpose of this commentary is discuss how musical intervention and imagined interactions can be used to deal with conflict. Music has been called the universal language because of its tonality and rhythm. It affects conflict and aggression and helps people to deal with stress. Research is reviewed showing physiological arousal with background music. The effects of music on aggression are summarized in terms of emotional regulation, catharsis and empathy, and the use of mental imagery in the form of imagined interactions, including relational maintenance catharsis and conflict linkage, is discussed. The incremental sound organizer (ISO) principle of music therapy is discussed as a mechanism to affect emotions while listening to music. Finally, a tool to measure the emotional effect of music on listeners is discussed in terms of the musical mood wheel.

This is a commentary on the effects of background music on reducing aggression.

Music can reduce aggression, depending on how it is used. Music affects how we manage our emotions, reduces stress, provides catharsis and can be a distracting element. Music can enhance empathic feeling; induce positive moods, social bonding, physiological changes and neurobiological changes; and affect our arousal.

Music therapy and musical intervention can be applied to conflict resolution.

The ISO principle of music therapy is designed to deal with changing a person’s emotions as they listen to a medley of music. The mood of the person is measured using a series of scales reflecting a continuum of sadness to happiness, and the music is designed to match the mood of the patient to the music being played and/or listened to, which in turn fosters the achievement of an altered state of consciousness. For example, if you are angry, start with music that is loud and gradually switch to a more tranquil piece of music. “The vectoring power of music is that we change the mood or emotion of persons from one affective pole (joy) to its opposite (anger) through small incremental changes in the rhythm and intensity of the music” (Honeycutt, 2003, p. 82).

Background music in music psychology literature is often referred to as musical intervention. Background music can help us recall positive and negative scenes as the music triggers endorphins in the brain (Salimpoor et al., 2011). Background music is intended to enhance the surrounding context without drawing significant attention. It is often played in spaces such as restaurants, stores, offices or public places to create a certain mood or ambiance.

It is important to note that the effectiveness of musical intervention in reducing aggression can vary based on individual preferences, the specific type of music used, and the context in which it is applied. Additionally, while music intervention can play a role in aggression reduction, it is often most effective when used as part of a comprehensive therapeutic approach.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

This paper highlights an assignment in a combination upper-division undergraduate and graduate civic leadership class at a Midwestern state comprehensive university. The three-part assignment challenges students’ critical thinking skills and research capabilities while simultaneously necessitating the exploration of contrasting viewpoints on contentious issues.

Intentionally exposing students to diverse perspectives in a controlled environment.

We posit that the severity and frequency of these issues can be mitigated through focused efforts.

Students are better prepared to engage in civil debate on controversial topics, which continuously divide our communities, after completing a class using this pedagogical strategy.

The use of insects as food is a proposed solution for the increased demand for food worldwide, but it lacks acceptance because of restrictive emotional factors. This article aims to understand better customers' emotions’ role in considering and consuming insect-based food.

To assess their acceptance, an experiment was developed with 38 participants living in Portugal to identify how people feel when consuming processed insect bars compared to cereal bars (of equal flavour). A video was recorded “before”, “during” and “after” the consumption of such foods, and the triggered emotions and affective states were identified using the Facial Action Coding System (FACS) and the circumplex model of affect, respectively. After consumption, the Self-Assessment Manikin (SAM) was asked to be completed.

It was observed that the valence and arousal of the emotions and affective states triggered during consumption were higher in the insect bar than in the cereal bar. Its consumption resulted in surprise and a positive evaluation. Processed insect-based foods may result in a potentially increased acceptance of this new food alternative in the market.

Prior studies briefly identified disgust as a primary emotion activated by insect-based food. The current research deeply studied emotional responses to insect-based processed foods in the Western world using the dimensional emotional models. This study offers arguments for the insect-based food industry to invest in processed food justified by its potential for acceptance. In addition, it motivates further research focused on other insect-based products (e.g. non-processed ones).

Many believe that any social media harms kids because of frequent use. This study aims to examine these assumptions. It proposes and tests a model that considers two alternative pathways – one negative and one positive – through which social media affects teens’ self-reported subjective well-being.

This research used Preacher and Hayes process modeling to conduct path analysis on data collected on 585 teenagers from across the USA.

Results showed that along a negative pathway, frequent social media use leads to greater risky social media engagement that ultimately diminishes adolescent’s sense of well-being. Also, and perhaps simultaneously, frequent social media use leads to socially-connected social media use that enhances adolescent’s sense of well-being.

The research recommends ways parents, policymakers and platforms can encourage teens to use social media to connect with friends while guiding them away from pathways exposing them to risky behaviors.

Findings show more social media use is not necessarily harmful, but more of some types is bad, while more of others is good.

The purpose of this study is to examine the behaviour of retail investors while making an investment decision and how it gets affected by the behavioural biases of the investors using a moderated-mediation framework.

A mixed method approach has been used to fulfil the objectives of the study. In the first study, a qualitative analysis of the interviews with 15 retail investors was conducted. As part of the quantitative study, a total of 201 responses from Indian retail investors were collected using systematic sampling and analysed using structural equation modelling and Process Macro.

The results indicate that anchoring bias, availability bias, herding bias, switching cost, sunk cost, regret avoidance and perceived threat have a significant effect on retail investors’ investing intention. The attitude of the investors towards investing decisions mediates the effects of behavioural bias and the status quo on investment intention. The results of the moderated-mediation analysis indicate that mediating effect of attitude varied at the low and high-risk aversion of investors.

The findings of this study will help regulators and retail investors to understand the critical behavioural biases which affect the investors’ investing intention.

The paper contributes to the literature on investors’ behaviour, status quo bias theory (SQB) and behavioural bias. This study uniquely proposes a moderated-mediation framework to understand the effects of biases on retail investors’ investment intention.