Search Results (181)

As augmented reality (AR) advertising becomes increasingly prevalent across digital platforms, understanding how its unique features influence consumer responses is critical for both theory and practice. Based on the elaboration likelihood model (ELM), this study develops and validates a dual-dimension content–dual-route processing model to investigate how different features of AR advertising influence consumer engagement. Specifically, it examines how product-related attributes (attractiveness, informativeness) and technology-related attributes (interactivity, augmentation) shape attitudes toward the ad and purchase intentions through cognitive (information credibility) and affective (enjoyment) pathways. Using data from an online survey (N = 299), the study applies partial least squares structural equation modeling (PLS-SEM) to test the proposed model. The results show that informativeness and augmentation significantly enhance information credibility, while attractiveness primarily influences emotional responses. Interactivity and augmentation positively influence cognitive and affective responses. Mediation analysis confirms the simultaneous activation of central and peripheral processing routes, with flow experience emerging as a significant moderator in selected pathways. By introducing a structured framework for AR advertising content, this study extends the applicability of the ELM in immersive media contexts. It underscores the combined impact of rational evaluation and emotional engagement in shaping consumer behavior and offers practical insights for designing effective AR advertising strategies. Full article

Background: Vaccine hesitancy (VH) represents a growing concern among healthcare professionals and students, potentially undermining public health efforts. Nursing, pediatric nursing, and midwifery students are future vaccinators and educators, making it essential to understand their attitudes, knowledge, and confidence toward vaccination. This study aims to assess vaccine-related perceptions and behaviors among these student populations in an Italian university. Methods: A cross-sectional survey was conducted between November 2022 and February 2024 at the University of Rome “Tor Vergata”. A structured, anonymous questionnaire, including the Vaccination Attitudes Examination (VAX) scale, vaccine knowledge items, and sources of information, was administered to students in nursing (n = 205), pediatric nursing (n = 46), and midwifery (n = 21). Statistical analyses included descriptive statistics, ANOVA, post hoc tests, and Mann–Whitney U tests. Results: Among the 272 participants, 20.6% reported refusing at least one recommended vaccine, and 18.4% delayed vaccination for non-medical reasons. Vaccine knowledge and confidence increased significantly with academic progression (p < 0.001). Midwifery students showed both the highest concern for long-term vaccine effects and the greatest confidence in vaccine safety. Institutional and scientific sources were the most trusted, though traditional and non-institutional media also influenced perceptions, particularly among midwifery students. Conclusions: Despite high COVID-19 vaccine uptake, VH persists among health professional students. Discipline-specific patterns highlight the need for early, targeted educational strategies to enhance vaccine literacy and reduce hesitancy. Tailored training may empower future professionals to become informed and credible advocates for vaccination. Full article

This research examines how influencer information spreads and is accepted by consumers, focusing on a Tunisian sample of social media users, and how these effects percolate into consumers’ perception of the quality of cosmetic products. Drawing on the Information Adoption Model (IAM), this study develops a conceptual framework adapted to the social media landscape, particularly the TikTok platform. To test this framework, we conducted a survey targeting 285 consumers using a non-random sampling frame, primarily through Facebook and Instagram. The findings suggest that consumers perceive influencer information as useful when they believe it is credible and of high quality. Interestingly, while high-quality information tends to lead to influencer information adoption, credibility alone does not guarantee adoption. Additionally, our study emphasizes the role of influencer information usefulness in driving its adoption. One notable discovery is the link between influencer information adoption and consumers’ perceptions of the quality of cosmetic products. However, this correlation does not hold equally for both genders, thus suggesting a moderation effect between gender and influencer information processing in this context. Full article

Social media platforms have become essential tools for businesses aiming to engage audiences through innovative communication, particularly in the food and beverage industry. This study explores the impact of three core digital marketing strategies, namely, social media advertisements, electronic word of mouth, and digital influencers, on customer responsiveness in the Lebanese food and beverage sector. Based on a cross-sectional survey of 400 participants, the findings reveal that social media advertisements significantly and positively influence customer responsiveness (β = 0.227, p < 0.001). Likewise, electronic word of mouth strongly predicts customer responsiveness (β = 0.453, p < 0.001), affirming the power of customer-generated content in shaping brand perceptions. Furthermore, the presence of digital influencers emerged as a significant predictor of consumer reaction (β = 0.236, p < 0.001), suggesting that consumers regard influencers as credible sources when making food-related decisions. Among all predictors, electronic word of mouth demonstrated the strongest effect. Control variables such as gender, age, and social media usage intensity showed no significant effect on customer responsiveness. These findings underscore the strategic value of rich media content and peer influence in shaping consumer behavior in the food and beverage industry. The study offers practical insights for marketers seeking to enhance customer engagement and brand responsiveness in digital spaces. Full article

AI-generated content has grown significantly in recent years. Today, AI-generated and human-made images coexist across various settings, including news media, social platforms, and beyond. However, we still know relatively little about how audiences interpret and evaluate these different types of images. The goal of this study was to examine whether image interpretation is influenced by the origin of the image (AI-generated vs. human-made). Additionally, we aimed to explore whether visual professionalization influences how images are interpreted. To this end, we presented 24 AI-generated images (produced using Midjourney, DALL·E, and Firefly) and 8 human-made images to 161 participants—71 visual professionals and 90 non-professionals. Participants were asked to evaluate each image based on the following: (1) the source they believed the image originated from, (2) the level of realism, and (3) the level of credibility they attributed to it. A total of 5152 responses were collected for each question. Our results reveal that human-made images are more readily recognized as such, whereas AI-generated images are frequently misclassified as human-made. We also find that human-made images are perceived as both more realistic and more credible than AI-generated ones. We conclude that individuals are generally unable to accurately determine the source of an image, which in turn affects their assessment of its credibility. Full article

Push notifications are a digital strategy for outlets to provide news and a convenient way for audiences to absorb information. Past research shows the effectiveness of push notifications and how they are framed, but few studies have explored their relationship with clickbait. However, clickbait often has a negative connotation. Through an exploratory mixed methods study involving textual analysis of push notifications (n = 639) sent by three credible mainstream media outlets, namely The Associated Press, The New York Times, and The Wall Street Journal, and a survey of readers’ (n = 368) perception of push notifications and clickbait, this research explores how credible news outlets directly engage with their respective audiences by framing push notifications in the form of clickbait. This study builds on framing theory by proposing the concept of credible clickbait and illustrating how push notifications shape readers’ immediate perceptions of content being shared with them by news outlets they subscribe to. This research also aims to be a resource for journalists to increase audience interaction and foster sustained attention with stories. Full article

Fashion live commerce has rapidly emerged as a compelling format that blends entertainment, real-time interaction, and product promotion. However, limited research has examined how specific experiential and perceptual factors influence consumer behavior in this context. This study aims to identify the key psychological and environmental drivers of satisfaction, continued platform use, and purchase intention among viewers of fashion live commerce. Using the stimulus–organism–response framework, this research focuses on the effects of perceived credibility, social media influencer characteristics, informativeness, internal shop environment, and monetary savings. Data were collected from 300 users of fashion live commerce platforms and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that all predictor variables significantly influence either satisfaction or current use, and both satisfaction and current use significantly predict purchase intention. Among the factors, satisfaction plays a central role, acting as a strong predictor for both current engagement and future buying decisions. These findings offer theoretical insights into consumer engagement in live commerce and provide practical guidance for streamers, marketers, and platform designers aiming to improve user experience and conversion rates. This study contributes to understanding the evolving dynamics of digital shopping environments shaped by social and emotional interactions. Full article

In regions with sustained air pollution, the adoption of protective health behaviors is critical, particularly among pregnant women—a population marked by physiological vulnerability and heightened receptivity to preventive guidance. Understanding and supporting patient-driven behavioral change requires attention to individual perception and awareness, which are shaped by socio-economic and spatial factors, as well as access to credible information. Objectives: This study investigates how pregnant women in Serbia perceive air quality, identifies determinants that influence these perceptions, and evaluates the extent and nature of behavioral adaptations undertaken to mitigate exposure-related risks. Methods: A cross-sectional survey was conducted among 279 pregnant women using a structured, researcher-administered questionnaire. Collected data included demographic and psychosocial variables, air quality perceptions, self-reported health effects, and behavioral responses. Residential proximity to land-use attributes was assessed using GIS-based spatial analysis. Results: Most participants perceived air quality as poor (68.8%), primarily informed by unofficial sources such as mobile applications and social media. Living close to continuous urban fabric (OR = 0.180, 95% CI: 0.059–0.558, p = 0.003) and water (OR = 0.306, 95% CI: 0.127–0.738, p = 0.008) was associated with poorer perceptions, while proximity to forests (OR = 2.938, 95% CI: 1.323–6.525, p = 0.008) correlated with more favorable assessments. Despite prevalent concern, around half of respondents (50.2%) reported no behavioral modifications. Importantly, none had received guidance from healthcare professionals on the topic. Conclusions: These findings highlight critical gaps in environmental health literacy and provider engagement. Integrating tailored communication and behavioral support in existing prenatal counseling could advance health-related quality of life in this vulnerable population. Full article

Earthquakes are sudden-onset disasters requiring rapid, accurate information for effective crisis response. Social media (SM) platforms provide abundant geospatial data but are often unstructured and produced by diverse users, posing challenges in filtering relevant content. Traditional content filtering methods rely on natural language processing (NLP), which underperforms with mixed-language posts or less widely spoken languages. Moreover, these approaches often neglect the spatial proximity of users to the event, a crucial factor in determining relevance during disasters. This study proposes an NLP-free model that assesses the spatial credibility of SM content by analysing users’ spatial trajectories. Using earthquake-related tweets, we developed a machine learning-based classification model that categorises posts as directly relevant, indirectly relevant, or irrelevant. The Random Forest model achieved the highest overall classification accuracy of 89%, while the k-NN model performed best for detecting directly relevant content, with an accuracy of 63%. Although promising overall, the classification accuracy for the directly relevant category indicates room for improvement. Our findings highlight the value of spatial analysis in enhancing the reliability of SM data (SMD) during crisis events. By bypassing textual analysis, this framework supports relevance classification based solely on geospatial behaviour, offering a novel method for evaluating content trustworthiness. This spatial approach can complement existing crisis informatics tools and be extended to other disaster types and event-based applications. Full article

This study explores the impact of DW’s news coverage on the perceptions, knowledge, and behavioural changes of the Syrian diaspora in Germany regarding the Syrian crisis. Grounded in the Uses and Gratifications theory, data were collected from 207 Syrian immigrants residing in Germany between September and November 2023 using a convenience sampling approach. The findings reveal that DW is perceived as a credible and objective news source that provides comprehensive and balanced coverage of the Syrian crisis. Exposure to DW’s reporting significantly enhanced respondents’ understanding of the crisis, enabling them to engage in informed discussions. DW’s coverage motivated behavioural changes, encouraging participation in social media discussions and humanitarian initiatives. This study highlights the critical role of trusted international media in shaping diaspora communities’ perceptions, knowledge, and actions during crises. These findings also highlight DW’s influence as a key information source for the Syrian diaspora, fostering both awareness and proactive engagement with the ongoing crisis. Full article

Social media sites, particularly Instagram, have recently developed effective instruments for influencing customer behavior, particularly regarding eating experiences and cuisine. This study examines the influence of posting food-related content on Instagram on customers’ intention to visit casual dining restaurants in Saudi Arabia. This study also examined the mediating role of credibility in shaping this intention. A quantitative approach was used through online surveys gathered from 685 Saudi Arabian customers. The major findings of this study revealed that foodstagramming attributes such aesthetic appeal (AA) and post popularity (PP) positively influence customers’ visit intention (VI) in the context of casual dining restaurants in Saudi Arabia. Furthermore, the content credibility (CC) of foodstagramming positively influences customers’ VI. In addition, the CC of foodstagramming partially mediates the relationship between AA, PP, and customers’ VI. Theoretical contributions and practical implications are also provided. Full article

Promoting public engagement through social media has always been a core issue in risk communication studies. Based on the Social Amplification of Risk Framework (SARF), this study conducts an online survey in China (N = 908) and constructs a moderated mediation model. Using bootstrapped moderated mediation analysis, this study examines the relationships among social media exposure to pandemic information, risk perception, source credibility, and public engagement on social media at the early stages of the pandemic. The results demonstrate a positive relationship between social media exposure and public engagement, which can be mediated by risk perception. The relationship between social media exposure and public engagement via risk perception is moderated by source credibility. The higher perceived credibility of official and interpersonal sources undermines risk perception, but also hinders public engagement in the crisis. The moderating effect of professional source credibility is not significant. This study has expanded the SARF and has contributed to promoting risk communication strategies from the perspective of risk information processing. Full article

Background/Objectives: Existing patient information leaflets (ePILs), mandated by the FDA to accompany new prescriptions, are difficult to read and understand due to their complexity and poor visual design, especially for populations with low health literacy and low English proficiency. In this study, we developed infographic-based PILs (iPILs) with a concise question-and-answer format, emphasizing essential information, as specified by the FDA. This study compared iPILs and ePILs using the 5C factors: comprehension, cosmetics, convenience, content, and credibility, as perceived by English-speaking and Spanish-speaking populations. Methods: This multicenter, experimental survey study assessed the 5C factors. English and Spanish-speaking adults on ≥1 chronic medication were recruited from community pharmacies in California (CA) and Illinois (IL). They were stratified to review either an ePIL or an iPIL for one of four common medications. They completed a Medication Knowledge Quiz (MKQ) to show their comprehension using six open-ended questions. Subsequently, they received both PIL versions and answered preference questions about the 4C and media format and, lastly, about demographic and health literacy questions. Results: A total of 235 participants completed the surveys at three sites (CA-English, CA-Spanish, and IL-English), with differing participant characteristics. The CA-Spanish participants scored the lowest on health literacy and the number of health conditions. The MKQ scores for those using the iPILs were significantly higher than for those using the ePILs across all groups. They significantly correlated with health literacy results for the ePILs (r = 0.394, p < 0.001). The participants preferred the iPILs over the ePILs for four of the C factors, barring one content question. Regardless of age, printed formats were preferred (64.7%)—alone or with digital formats (21.3%)—over digital formats alone (3.4%). Overall, 79.1% of the participants preferred iPILs, 11.9% preferred ePILs, and 8.9% preferred either version. Conclusions: The infographic-based patient information leaflets (iPILs) were easier to read, navigate, and understand, making them more accessible to individuals with varying levels of health literacy. Infographic-based leaflets outperformed existing ones in user comprehension and were preferred due to their simple layout, ease of navigation, and helpfulness. Full article

In the digital age, climate change content on social media is frequently distorted by misinformation, driven by unrestricted content sharing and monetization incentives. This paper proposes a novel AI-based framework to evaluate the data quality of climate-related discourse across platforms like Twitter and YouTube. Data quality is defined using key dimensions of credibility, accuracy, relevance, and sentiment polarity, and a pipeline is developed using transformer-based NLP models, sentiment classifiers, and misinformation detection algorithms. The system processes user-generated content to detect sentiment drift, engagement patterns, and trustworthiness scores. Datasets were collected from three major platforms, encompassing over 1 million posts between 2018 and 2024. Evaluation metrics such as precision, recall, F1-score, and AUC were used to assess model performance. Results demonstrate a 9.2% improvement in misinformation filtering and 11.4% enhancement in content credibility detection compared to baseline models. These findings provide actionable insights for researchers, media outlets, and policymakers aiming to improve climate communication and reduce content-driven polarization on social platforms. Full article

As social media platforms become integral to information dissemination, they play a crucial role in shaping tourist decision-making and travel behavior. However, while previous studies have examined the general influence of social media on tourism, limited research has explored the interplay between source attributes, content quality, destination image, and trust in fostering impulsive travel intentions, a key yet underexplored aspect of tourist behavior. To address this gap, this study integrates the Stimulus–Organism–Response (SOR) theory and the Information Adoption Model (IAM) to analyze how source credibility, source homophily, and content quality on social media influence impulsive travel intentions through destination image and trust. Using structural equation modeling (SEM) on survey data from 419 Chinese respondents, the results reveal that source credibility and homophily significantly enhance content quality, while both credibility and content quality positively shape destination image. Moreover, destination image and trust serve as crucial mediators, strengthening the relationship between social media attributes and impulsive travel behavior. This study advances the discourse on sustainable tourism development by shedding light on the role of digital engagement in shaping tourists’ spontaneous travel decisions, a dimension often overlooked in discussions on long-term economic sustainability. Furthermore, by examining the nuanced mechanisms of social media influence, this research provides practical implications for tourism marketers and policymakers aiming to leverage digital platforms for sustainable destination marketing. Full article