Search Results (1,377)

YouTube is the most popular social media platform for children and adolescents, yet relatively little research has been conducted on adolescents’ use and their motivations for use. Prior research has predominantly focused on measuring the quantity of time spent on the platform, and less is known about the motivations and self-awareness of using YouTube as children turn into tweens and teens. Stemming from a larger survey study of adolescent social technology use, we interviewed a subset of 35 youths (50% female, 49% male, 1% non-binary) to qualitatively explore the benefits and challenges of YouTube use. Thematic analyses revealed the wide range of emotional responses and regulation that were attributed to YouTube use, including humor, fear, anger, insecurity, and anxiety. Some participants experienced wishful identification with YouTube influencers, and others viewed YouTube as entertainment or an escape from boredom. Sleep regulation was mixed, in that for some, YouTube was a distraction from getting enough sleep, and for others, it helped them fall asleep. Parental monitoring was a developmental challenge as the youths described their parents as lacking knowledge about the length of time they spend on the platform and/or the risky YouTube content that they watch, particularly as they got older. These exploratory findings may be pertinent for parents, educators, and clinicians. Full article

This study investigates the influence of experiential programs (EPs) on enhancing consumer experience offerings at luxury resorts. EPs encompass a variety of activities, amenities, and services designed to immerse consumers in the local culture, scenery, and authenticity. The research focuses explicitly on EPs related to fitness, evening entertainment, children’s activities, and personalized experiences. By analyzing data from 30 resorts, significant trends and typologies within each category of EP emerged, highlighting the diverse ways in which resorts meet consumers’ desires for immersive and status-enhancing experiences. Valuable insights were gained through semi-structured interviews with two hoteliers, providing a deeper understanding of the strategic integration of EPs. Fitness EPs highlight activities, including hiking and yoga, whereas evening entertainment encompasses experiences like mixology, music, and astronomy education. For children, EPs prioritize cultural immersion through hands-on experiences, while personalized EPs—including romance packages and private dining—allow for consumer exclusivity. The research underscores how these EPs align with contemporary trends in conspicuous consumption, where luxury resorts leverage unique, high-quality, and culturally rich experiences to reinforce affluence and societal standing. The findings emphasize that EPs are a vital strategy for luxury resorts to differentiate themselves in a competitive market, enhancing consumer satisfaction, loyalty, and positive self-image. Full article

Whether it is asking Alexa to set a reminder or having Google Assistant place a call, AI-powered assistants are becoming an increasingly seamless part of our daily lives. This study aims to address what predicts the users’ satisfaction with Alexa by analyzing the using motives, cognitive involvement, and emotional involvement of its consumers. The variables include using motives, attention, elaboration, emotional involvement, and usage satisfaction. Alexa users (N = 299) completed a brief online survey, including Scales of Using Motives for Media, the Perceived Attention Scale, the Elaboration Scale, the Mood Adjective Check List Scale, and Television Viewing Satisfaction Scale. Participants who were at least eighteen years of age and owned and used Alexa were included in this study. An exploratory factor analysis revealed four distinct types of motivation for using Alexa: Companionship, Entertainment–Information, Work-Efficiency, and Pastime. The results from hierarchical regressions showed that Alexa usage satisfaction was predicted by Entertainment–Information and feeling positive emotions while using. Full article

Background/Objectives: This study aimed to identify the relationships between individuals’ perceptions of leisure boredom, internet usage habits, and gambling motivations, focusing on analyzing the predictive effects by age category in adults. Methods: The study employs quantitative research methods, adopting a relational survey model. The sample group comprises 310 adult (94 female and 214 male) individuals aged 18 and over. Data were collected using the Leisure Boredom Scale (LBS), targeting two subscales: negative (Boredom) and positive (Satisfaction) attitudes toward leisure time, the Leisure Internet Use Scale (LIUS) targeting four forms of leisure, and the Gambling Motivation Scale (GMS) with the following subscales: socialization, entertainment/excitement, escapism, and money-making. In the analysis conducted with SPSS 25.0, independent samples t-test, ANOVA, correlation, and regression analyses were applied. Results: The findings indicate that leisure boredom significantly predicts internet usage and gambling motivations. Notably, individuals who spend their leisure time on passive activities were found to have higher rates of internet usage, habits, digital addiction, and gambling behavior. The positive relationship between internet usage habits, digital addictions, and risky behaviors such as gambling becomes particularly pronounced among young adults. Conclusions: Leisure time management is critical for individuals’ psychological well-being. Cognitive awareness programs, digital literacy education, and promoting participation in healthy leisure activities are recommended as key strategies to prevent risky behaviors. Full article

Over the past two decades, transitional justice has become a central concern in Taiwan’s cultural and political landscape. This study investigates how 1029 visitors from Taiwan, Sinophone regions (China, Hong Kong, Macau, Malaysia), and international backgrounds engage with digital interpretation systems at the Chiang Kai-shek Memorial Hall (CKSMH)—a politically sensitive site associated with Taiwan’s authoritarian past. Using a mixed-methods approach combining surveys and qualitative responses, the study analyzes cross-cultural differences in visitor motivation, use of digital tools, perceived experiential value, satisfaction, and behavioral intention. Results show that international visitors reported higher levels of engagement and satisfaction, particularly in educational, esthetic, entertainment, and escapist dimensions. In contrast, Sinophone visitors expressed lower satisfaction and more frequent discomfort with the site’s historical narrative. Key factors such as language accessibility, cultural proximity, and usability influenced how visitors perceived the digital content. The findings suggest that interactive digital tools can support both cultural engagement and critical reflection while also revealing tensions in memory politics at sites of transitional justice. Full article

Theaters in ancient Pompeii played a vital role in Roman entertainment, shaping the auditory experiences of spectators. This study examines the acoustic properties of the Amphitheater, the Grand Theater, and the Odeon using impulse response (IR) analysis to reconstruct their soundscapes. Next, the study considers the impact of typical musical instruments, vocal performances, and ambient sounds—such as gladiatorial combat—on these spaces’ acoustics. Findings reveal significant differences in reverberation times, sound clarity, and spatial characteristics, shaped by each theater’s design. These sites, preserved after the eruption of Mount Vesuvius, provide a unique opportunity to analyze how architecture influenced sound propagation. The Amphitheater, with its vast open structure, enhanced large-scale events, while the Grand Theater’s semi-enclosed design balanced musical and theatrical performances. The Odeon, the most intimate of the three, prioritized speech clarity. These insights highlight how Roman architects engineered performance spaces to accommodate diverse entertainment forms. By combining acoustic measurements with historical context, this research offers a deeper understanding of ancient Pompeii’s soundscapes and the auditory experiences of its inhabitants and offers insights for composition and soundscape creations that take inspiration from these prominent historical architectural and cultural icons whilst exploring its potential within contemporary immersive listening practices. Full article

Electroencephalography (EEG) is a non-invasive and portable way to capture neurophysiological activity, which provides the basis for brain–computer interface systems and more innovative applications, from entertainment to security. However, the acquisition of EEG signals often suffers from noise contamination and even signal interruption problems due to poor contact of the electrodes, body movement, or heavy noise. Such heavily contaminated and lost signal segments are usually removed manually, which can hinder practical system deployment and application performance, especially in scenarios where continuous signals are required. In our previous work, we proposed the weighted gate layer autoencoder (WGLAE) and demonstrated its effectiveness in learning dependencies in EEG time series and encoding relationships among EEG channels. The WGLAE adopts a gate layer to encourage the AE to approximate multiple relationships simultaneously by controlling the data flow of each input variable. However, it only applies a sequential control scheme without taking into account the physical meaning of EEG channel locations. In this study, we investigate the gating mechanism for WGLAE and validate the importance of having a proper gating scheme for learning relationships between EEG channels. To this end, several gate control mechanisms are designed that embed EEG channel locations and their corresponding underlying physical meanings. The influences introduced by the proposed gate control mechanisms are examined on an open dataset with different scales and associated with various stimuli. The experimental results suggest that the gating mechanisms have varying influences on reconstructing EEG signals. Full article

LEGO^® Serious Play^® (LSP) was used to understand the ideals of connectivity and inclusivity among students, adult learners, and workers in a higher education community. While connectivity in nature’s ecosystem has been well studied, it is important to explore this form of connectivity among humans. The objectives of this study were to determine and analyze the main barriers and enablers of connectivity and inclusivity in higher education teaching, learning, and operations, and to propose key action plans. By using LSP in our study, we explored a kinesthetic approach where participants from diverse age groups (20–56 years) and professional/academic levels built models and shared their stories with others. An evaluation of the workshop was obtained using questionnaires (open-ended and scale-based surveys). All the participants found the LSP useful for the overall experience, indicating a strong overall support for its use. In total, 75% of the participants found it valuable and 50% of the participants found the process “difficult”, particularly in group communication and model representation, which require further refinement. Participants’ responses showed that both affective and cognitive elements were active during the workshop, suggesting that this method encourages all voices to be heard. In addition, the methodology for problem-solving and entertainment is a promising pedagogical and andragogical tool for teaching in higher education and in non-academic settings. Full article

Coastal tourism benefits the sustainability of destinations and includes a wide range of experiences related to sun and sand, culture, nature, and social interactions. This study aimed to (i) identify the motivations driving tourists to coastal destinations, (ii) determine the tourist segments in these destinations, and (iii) examine the relationship between these tourist segments and satisfaction and loyalty. The research was conducted in Montañita, Ecuador, a renowned surfing and water sports destination frequented by both national and international tourists. The sample consisted of 380 valid questionnaires, analyzed using factor analysis, K-means clustering, and Pearson’s chi-square test. The findings revealed five motivational dimensions: Culture and Nature, Novelty and Social Interaction, Sun and Beach, Sports, and Entertainment. Two distinct tourist segments were also identified: Multiple Motives tourists and Sun and Beach tourists. Among these, the Multiple Motives group exhibited higher levels of satisfaction and loyalty. These insights are valuable for destination managers and tourism service providers, offering practical applications for enhancing visitor experiences. Additionally, this study contributes to the existing academic literature on coastal tourism. Full article

With the rapid development of deep learning in artificial intelligence, sequential recommendation systems play an increasingly important role in e-commerce, social media, digital entertainment, and other fields. This work systematically reviews the research progress of deep learning in sequential recommendation systems from a methodological perspective. This paper focuses on analyzing three dominant technical paradigms: contrastive learning, graph neural networks, and attention mechanisms, elucidating their theoretical innovations and evolutionary trajectories in sequential recommendation systems. Through empirical investigation, we categorize the prevailing evaluation metrics, benchmark datasets, and characteristic distributions of typical application scenarios within this domain. This work further proposes promising avenues for sequential recommendation systems in the future. Full article

This study aims to explore how key opinion leader (KOL) characteristics influence users’ purchase intentions in live shopping. Using a mixed-methods approach, the study combines real-time pop-up text mining and questionnaires, analyzed via Latent Dirichlet Allocation (LDA) topic modeling and a research framework integrating the stimulus–organism–response (SOR) model with pleasure–arousal–dominance (PAD) theory. Results indicate that KOL characteristics—namely professionalism, popularity, attractiveness, and entertainment—enhance users’ pleasure, arousal, and trust. These emotions boost impulse buying intentions but not planned ones. Planned purchase intention acts as a partial mediator, whereas impulse purchase intention serves as a full mediator. This research uncovers the intricate mechanism linking KOL traits to user emotions and purchase intentions. By integrating PAD theory and the SOR model, it examines emotional mediators, addresses prior theoretical gaps, offers vital insights for refining live-streaming marketing strategies, and holds substantial theoretical and practical significance for the sustainable growth of live-streaming e-commerce. Full article

This study explores the relationship between perceived quality and happiness among self-driving tourists, focusing on the impact of the self-driving journey and sightseeing stages on multi-stage satisfaction and happiness. An online survey was conducted, and a Structural Equation Model (SEM) of perceived quality, satisfaction, and happiness was constructed to test the hypotheses. The results indicate that overall satisfaction with the self-driving experience significantly affects tourists’ happiness, with the indirect effect of attraction satisfaction being particularly notable. Perceived quality indirectly influences happiness by enhancing satisfaction, with key factors including unique attractions, guide services, and innovative entertainment products. Additionally, the development of self-driving parking facilities, public information dissemination, road key nodes and scenery design, and vehicle intelligence levels are critical to enhancing tourists’ happiness. This study provides a theoretical basis for improving the overall tourism experience. Full article

The current study aims to explore the early adoption of the metaverse in the hospitality and tourism industry, with a particular focus on understanding adoption drivers for tourism providers and the anticipated benefits for end-users. Addressing the need for practical insights in a rapidly evolving digital landscape, the review identifies 33 real-world early cases of metaverse and non-fungible token (NFT) adoption, spanning from the first metaverse hotel in 2006 to ongoing digital twins of tourism destinations up to 2023. This study follows the PRISMA technique and examines early metaverse adopters at both the enterprise and destination levels, categorizing them into metaverse-based, NFT-based, and complementary-to-tourism cases. The analysis applies two theoretical frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine adoption drivers and the Technology Acceptance Model (TAM) to assess expected end-user benefits. Key findings highlight promotion, brand engagement, new revenue streams, and community building as primary motivations for adoption, while user benefits include enhanced entertainment, social interaction, improved decision-making, and immersive experiences. By bridging theory and practice, this study contributes both actionable guidance for tourism stakeholders and a theoretical foundation for future research on digital transformation in tourism. Full article

Gaming is one of the largest industries of digital entertainment. Modern gaming software may be susceptible to command execution delay, which may be caused by various factors, such as insufficient rendering capabilities or limited network resources. At the time of writing this paper, the utilized advances in gaming are often accompanied by brief descriptions when communicated to the users. While such descriptions may be compressed into a couple of words, even a single word may impact user experience. Due to the cognitive bias induced by the labeling effect, the impact of such a word may actually be more significant than what the user genuinely perceives. In this paper, we investigate the influence of the labeling effect on the perception of command execution delay in gaming. We carried out a series of subjective tests to measure how the word “optimized” affects gaming experience. The test variables of our experiment were the added delay between command and execution, the speed of the game, and the label that was assigned to gaming sequences. The test participants were tasked to directly compare gaming sequences with the different labels assigned: “optimized” and “not optimized”. In every comparison, both sequences had the same objective characteristics; only the label differed. The experiment was conducted on single-input and continuous-input computer games that we developed for this research. The obtained results indicate that for both of these input types, the labeling effect has a statistically significant impact on perceived delay. Overall, more than 70% of the subjective ratings were affected by the assigned labels. Moreover, there is a strong correlation between the amount of delay and the effect of cognitive bias. The speed of the game also affected the obtained results, yet statistically significant differences were only measured between the slowest and the fastest gameplay. Full article

Automated motion evaluation has become popular in exercise training and entertainment. In this study, an advanced automatic dance scoring algorithm is proposed. First, to avoid misjudgment from misalignment, space and time alignment are assessed. Then, instead of using the whole video frames as the input, we apply the joint information, including the relative locations, the moving velocities, the orientations, and the areas between the joint lines. To make the features more flexible and magnify the detail difference, we take the fractional powers on input features. The correlation coefficients are calculated for feature selection, and a nonlinear analysis is introduced to determine the angle difference. The least mean square error approximation is also applied to determine the linear combination coefficients of the features. The difference between the ground truth and the interpolated results from the regression line is minimized using the input features. The proposed algorithm accurately predicts dancing scores. Full article