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Immersive technologies fully immerse users in augmented environments for interactive experiences. The purpose of this study is to measure consumers’ intention towards experiencing immersive technologies at tourism destinations using an integrated theory of planned behaviour (TPB) and technology acceptance model (TAM) model within the stimulus-organism-response (S-O-R) framework, including motivation (MOT), trust (TR) and perceived risk (PR).

The survey data was collected through convenience sampling via an online questionnaire, with a sample size of 487 Indians. Structural equation modelling was conducted using SPSS and AMOS software for data analysis, ensuring a robust examination of the proposed model and its relationships.

Virtual interactivity and social interaction influence both attitude and perceived behavioural control. Attitude, perceived behavioural control, perceived usefulness and TR significantly influence intention. However, MOT, PR and perceived ease of use do not exhibit a significant influence on intention. These findings highlight the importance of these variables in shaping consumers’ intention towards experiencing immersive technologies at tourism destinations.

The findings hold significant implications for various stakeholders, including government agencies, travel firms, content creators and software developers. They can leverage these insights to enhance marketing strategies, develop immersive tourism experiences, innovate in the realm of Web 4.0 and personalize tourism offerings.

This study offers a distinctive contribution by integrating the S-O-R framework with TPB and TAM, while also incorporating key factors such as MOT, TR and PR. This novel approach provides a fresh perspective on consumer behaviour towards immersive technologies.

Fashion companies have been among the first to ride the new trend and develop projects for the Metaverse, considering Generation Z (Gen Z) as a relevant target. The paper aims to investigate Gen Z consumers’ intention to use digital fashion items in the Metaverse.

The study relies on the technology acceptance model (TAM). The authors include specific aspects of the Metaverse: the user-avatar identification and the development of an alternative identity; fashion innovativeness is discussed as a moderator variable. The model is tested on Gen Z consumers, with 329 survey responses collected in 2022 and analyzed using structural equation modeling (SEM).

The paper shows that the two external and explanatory variables the authors added, i.e. user-avatar identification and alternative identity, positively and directly impact the individual attitude to use digital fashion items in the Metaverse. Moreover, according to the proposed research model, the moderating effect concerning fashion innovativeness has positive and negative consequences.

Using TAM, the authors explored consumers’ perceptions (perceived usefulness and ease of use), attitudes and intentions regarding the new technology context (digital fashion in the Metaverse). This study enriched TAM with new consumer marketing constructs (user-avatar identification and alternative identity) and their relationships with consumers’ intention to use digital fashion items in the Metaverse. This study also contributed to TAM by exploring the relevance of moderating the effects of consumer fashion innovativeness on consumers’ intentions and attitudes in the novel context of digital fashion in the Metaverse. The paper contributes to the academic debate by focusing on the individual and personal sphere of the consumer moving in the Metaverse digital environment. The marketing-focused study develops research on Gen Z consumers to provide new insights and possible opportunities for marketers in the Metaverse.

Mental health is not simply the absence of psychological problems any more than physical health is the absence of disease. This chapter explores various aspects of optimal mental health and wellbeing among college students. It examines the question of what is required for college students to both feel their best and function at or near their highest levels. It also discusses the characteristics of peak mental health, including its transient nature. Predictive factors such as exercise, diet, sleep and social connection will be explored. Regarding the features of optimal wellbeing, the following variables are described: integrity, values, mindfulness, self-compassion, flow and resilience. These variables are considered in an integrated fashion as components, as well as byproducts, of wellness. Hettler’s multidimensional model of wellness is presented at the outset of the chapter, followed by Keyes’ theory of flourishing.

Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers.

We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers.

The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers.

This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.

Credible influencers play a key role in shaping the views and preferences of social media users. However, many influencers intentionally use disinformation (e.g. false narratives) to deceive users and gain their trust. This can have serious repercussions, not only for the firms that associate with these influencers but also for users. Further, and alarmingly, many influencers who use disinformation can sustain their credibility over time. This research explores how influencers use disinformation to establish long-term credibility on social media.

Drawing on self-presentation theory, we use an in-depth qualitative case study to address our research question, primarily relying on archival data obtained from multiple sources.

Our findings suggest that three stages of self-presentation are required to establish influencer credibility based on disinformation: backstage (preparing to deceive), experimentation (testing deception), and frontstage (launching deceptive ideas on a large scale). We also find that when fraudulent influencers simultaneously weaponise a counterculture and mindfully encase disinformation, users view them as highly credible.

We offer practical suggestions for regulating fraudulent influencers, including enacting fact-checking procedures, using IT artefacts as reliability signals, and building awareness programmes to develop vigilance in social media communities.

We contribute to self-presentation theory by adding experimentation as a critical stage in developing disinformation that works for long periods. We also contribute to the literature at the intersection of social media influencers and disinformation research by revealing why social media users believe in fraudulent influencers.

The aim of this paper is to explore the effect of telepresence, social presence and consumer involvement on intention to purchase, with an intervening impact of three dimensions of consumer brand engagement (cognitive processing, affection processing and activation).

The study followed a surveying technique and an adopted questionnaire was used to collect data from 426 shoppers of apparels. The model was tested using Smart PLS and it was found that there is a positive relationship between telepresence, social presence and consumer brand involvement with consumer brand engagement, which also mediates their relationship with intention to purchase.

This study offers analytical evidence for telepresence, social presence and involvement of customers and advances the literature of brand engagement. Marketers can benefit from this study and design their future campaigns to enhance the involvement of customers by utilizing the outcomes of this study.

This study offers analytical evidence for telepresence, social presence and involvement of customers and advances the literature of brand engagement. Marketers can benefit from this study and design their future campaigns to enhance the involvement of customers by utilizing the outcomes of this study.

Social media marketing has become a powerful strategic tool for many brands, but scholarly research in this domain is still in its infancy. This study aims to examine the effects of social media marketing activities on consumer online impulse buying intentions via brand resonance and emotional responses by incorporating the direct and moderating effects of social network proneness toward fashion retail brands.

By using snowball sampling, this study recruited 441 netizens (who were using fashion retail brands) and obtained their responses through an online survey. Structural equation modeling was applied to 394 responses for analysis.

The findings discovered that social media marketing activities significantly influenced brand resonance, consumer emotional responses and online impulse buying intentions. Likewise, brand resonance and emotional responses were positively associated with online impulse buying intentions and acted as decisive mediators. Social network proneness’s direct and moderating effects significantly increased consumer online impulse-buying intentions toward fashion retail brands.

This study provides recommendations to retail managers for creating and executing brand positioning, segmenting and targeting strategies to enhance consumers’ intentions for engaging in online impulsive purchases for fashion brands.

This original research contributes to the branding literature and stimulus–organism–response theory by focusing on social media marketing activities, brand resonance, emotional responses, social network proneness and consumer online impulse buying intentions toward fashion retail brands.

This study aims to meta-analytically investigate the impact of educational technology interventions on the development of creative thinking in educational settings. In recent years, the debate among researchers has persisted regarding the impact of various educational technologies, including interactive learning environments, digital instruction and platforms, and educational games and robotics, on students' creative thinking in diverse educational settings due to inconsistent findings.

This study, conducting a meta-analysis by synthesizing 35 relevant empirical studies with 2,776 participants, aims to investigate the association between educational technology interventions and the Torrance Tests of Creative Thinking (TTCT) and its subscales (fluency, flexibility, originality and elaboration).

No evident publication bias was found. From a general perspective, the results demonstrate a moderate level of influence of educational technology on the overall TTCT scale, with high heterogeneity attributed to the adopted instruments, mixed methods and target outcomes. Additionally, the results indicate that only three of the TTCT subscales (fluency, flexibility and originality) are influenced by educational technologies. Among the interventions, interactive learning environments yielded medium to the largest mean effect size. Furthermore, moderator analyses suggest that the effects of interventions on two subscales of TTCT (flexibility and originality) are moderated by school types, research design and the duration of intervention. The conclusion drawn is that interventions promoting students' creative thinking in different educational settings are efficacious.

Despite the low homogeneity of the results, which might have influenced the findings, the large fail-safe N suggests that these findings are robust. The study examined potential causes of heterogeneity and emphasized the importance of further research in this area.

Advances in digital technologies and the growing number of touch points have had a significant impact on the shopping behaviour of omnichannel customers. Several research papers have explored different facets of omnichannel, but only a few have thoroughly explored the literature on showrooming and webrooming simultaneously. This paper aims to identify the key groups of antecedents influencing customer buying behaviour in omnichannel, under the influence of digital technologies, with a particular focus on showrooming and webrooming.

Our study conducted a systematic literature review to identify the factors influencing customers’ buying behaviour in omnichannel, which have been the subject of academic discussion over the last decade. We finalized 149 articles for the thematic analysis and identified three groups of antecedents: channel-related, product-related and consumer-related with their subgroups.

Under channel-related antecedents, cost and perceived benefits, search convenience, need for interaction and situational circumstances have been identified as major attributes. The expressiveness of the product, product demonstration and search and experienced products have been identified under product-related antecedents, followed by price consciousness, past experiences, perceived risks and shopping motivations as leading attributes under consumer-related antecedents. The study revealed the multifaceted influence of digital technologies on omnichannel buying behaviour. Digital technologies are shaping the antecedents related to channels, products and consumers. Digital technologies simultaneously mediate between antecedents and the selection of a specific path within an omnichannel environment. Showrooming and webrooming should no longer be seen as general concepts. The rise of digital technologies has led to the development of new consumer journey patterns and the blurring of distinctions between showrooming and webrooming. A conceptual framework has been proposed to understand consumers' omnichannel behaviour, having considered the identified antecedents and the role of digital technologies.

This study advances the academic understanding of consumer behaviour in omnichannel under the influence of digital technologies and provides important implications for omnichannel management. With the advancement of digital technologies such as augmented reality and virtual reality, retailers should implement channel integration strategies to bridge the gap between online and offline channels, providing a memorable shopping experience for omnichannel customers.

This study is unique because it identifies and analyses the antecedents of consumer behaviour in omnichannel settings under the influence of digital technologies. It also uncovers new potential combinations of showrooming and webrooming patterns. The proposed framework can help retailers in their future planning of omnichannel strategies.