Search Results (339)

As ad-supported subscription models proliferate across over-the-top (OTT) media platforms, understanding the psychological mechanisms and perceptual factors that underlie consumers’ transition decisions becomes increasingly consequential. This study integrates the Uses and Gratifications framework with a contemporary motivation-based perspective to examine how users’ media consumption motivations and advertising attitudes predict intentions to adopt ad-supported OTT plans. Data were collected via a nationally representative online survey in South Korea (N = 813). The sample included both premium subscribers (n = 708) and non-subscribers (n = 105). The findings reveal distinct segmentation in decision-making patterns. Among premium subscribers, switching intentions were predominantly driven by intrinsic motivations—particularly identity alignment with content—and by the perceived informational value of advertisements. These individuals are more likely to consider ad-supported plans when ad content is personally relevant and cognitively enriching. Conversely, non-subscribers exhibited greater sensitivity to extrinsic cues such as the entertainment value of ads and the presence of tangible incentives (e.g., discounts), suggesting a hedonic-reward orientation. By advancing a dual-pathway explanatory model, this study contributes to the theoretical discourse on digital subscription behavior and offers actionable insights for OTT service providers. The results underscore the necessity of segment-specific advertising strategies: premium subscribers may be engaged through informative and identity-consistent advertising, while non-subscribers respond more favorably to enjoyable and benefit-laden ad experiences. These insights inform platform monetization efforts amid the evolving dynamics of consumer attention and subscription fatigue. Full article

In the attention-driven environment of online video platforms, understanding the factors that influence content selection and channel subscriptions is crucial for creators, marketers, and platform managers. This study investigates how thumbnails, view counts, video length, genre, and the number of advertisements affect user decision-making on YouTube. Grounded in random utility theory and reference-dependent preference theory, this study conducted a choice experiment with 525 respondents and employed a combined model of rank-ordered and binary logit methods to analyze viewing and subscription behaviors. The results indicate a significant preference for thumbnails with subtitles and shorter videos. Notably, we found evidence of reference-dependent effects, whereby a higher-than-expected number of ads decreased viewing probability, while a lower-than-expected number significantly increased subscription probability. This study advances our understanding of the factors that influence user behavior on social media, specifically in terms of viewing and subscribing, and empirically supports prospect theory in the online advertising market. Our findings offer both theoretical and practical insights into optimizing video content and monetization strategies in competitive social media markets. Full article

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

Certain industries will bear a disproportionate share of the burden of climate change. Climate change risk perceptions can impact workers’ mental health and well-being; increased climate change risk perceptions are also associated with more favourable adaptive attitudes. It is, therefore, important to understand whether climate risk perceptions differ across workers between industries. We conducted an online survey of British Columbians (16+) in 2021 using social media advertisements. Participants rated how likely they believed their industry (Natural Resources, Science, Art and Recreation, Education/Law/Government, Health, Management/Business, Manufacturing, Sales, Trades) would be affected by climate change (on a scale from “Very Unlikely” to “Very Likely”). Ordinal logistic regression examined the association between occupational category and perceived industry vulnerability, adjusting for socio-demographic factors. Among 877 participants, 66.1% of Natural Resources workers perceived it was very/somewhat likely that climate change would impact their industry; only those in Science (78.3%) and Art and Recreation (71.4%) occupations had higher percentages. In the adjusted model, compared to Natural Resources workers, respondents in other occupations, including those in Art and Recreation, Education/Law/Government, Management/Business, Manufacturing, Sales, and Trades, perceived significantly lower risk of climate change-related industry impacts. Industry-specific interventions are needed to increase awareness of and readiness for climate adaptation. Policymakers and industry leaders should prioritize sectoral differences when designing interventions to support climate resilience in the workforce. Full article

This study explores the application of spiking neural networks (SNNs) for click-through rate (CTR) prediction in personalized online advertising systems, introducing a novel hybrid model, the Temporal Rate Spike with Attention Neural Network (TRA–SNN). By leveraging the biological plausibility and energy efficiency of SNNs, combined with attention-based mechanisms, the TRA–SNN model captures temporal dynamics and rate-based patterns to achieve performance comparable to state-of-the-art Artificial Neural Network (ANN)-based models, such as Deep & Cross Network v2 (DCN-V2) and FinalMLP. The models were trained and evaluated on the Avazu and Digix datasets, using standard metrics like AUC-ROC and accuracy. Through rigorous hyperparameter tuning and standardized preprocessing, this study ensures fair comparisons across models, highlighting SNNs’ potential for scalable, sustainable deployment in resource-constrained environments like mobile devices and large-scale ad platforms. This work is the first to apply SNNs to CTR prediction, setting a new benchmark for energy-efficient predictive modeling and opening avenues for future research in hybrid SNN–ANN architectures across domains like finance, healthcare, and autonomous systems. Full article

In the context of accelerating digitalization, this study investigates how electronic commerce performance is influenced by Web 2.0 instruments in the 27 EU member states. Analyzing literature reviews and performing our own bibliometric review, we identified a gap related to the measurable economic results of e-commerce. The scope of this study was to analyze the relationship between Web 2.0 tools and the level of turnover generated by e-commerce, applying robust econometric models based on panel data regression with random effects and fixed effects (Arellano–Bond). The results highlight that the online paid advertisement and social media usage variables have significant, positive effects on e-commerce performance, confirming the first and second hypotheses. “Use the enterprise’s blog or microblogs” and “use of multimedia content sharing websites” do not influence enterprises’ total turnover from e-commerce sales to a valid and statistically significant extent. Thus, the third and fourth hypotheses are not confirmed by the results of the research conducted, possibly due to limited innovation and platform ownership in Europe. This study makes a notable empirical and methodological contribution, embedding digital sustainability in the analysis, which implies that the findings can be used for updating e-commerce policies. Full article

A growing knowledge base highlights the importance of accounting for a variety of social and structural determinants of health (SDOH) when understanding mental and behavioral health among adolescents and young adults. The objective of the current study is to examine patterns of self-reported SDOH deficits and characterize participant health indicators and social identity across classes. Data is from a cross-sectional national study of young people who were recruited through study advertisements on social media and surveyed online. Data were collected between June 2022 and October 2023. Eligibility included (1) ages 13–22 years, (2) living in the United States, and (3) proficient in English. Health indicators included suicide attempts, suicidal ideation, drug overdose, perceived likelihood of living to age 35, non-suicidal self-injury, recent alcohol use, and depression. Five classes of SDOH deficits were identified: (1) Economic Instability, (2) Low Overall SDOH Deficits, (3) High Social SDOH Deficits (adversity and discrimination), (4) High Economic SDOH Deficits, and (5) High Overall SDOH Deficits. Differences across class by health indicators and marginalized identity were found, with high proportions of gender minority and sexual minority youth in both the High Overall SDOH Deficit group and the High Social SDOH Deficit classes. Black youth were more likely to be part of the High Economic SDOH Deficits class. The findings encourage a public health approach that recognizes that improving the health of today’s young people must be connected to policies that reduce poverty, improve neighborhoods, and increase access to basic goods, services, and healthcare. Full article

In today’s hyperconnected world, disaster announcements—regardless of actual impact—can significantly shape consumer behaviour and brand perception in the hospitality sector. This study investigates how customers respond online to disaster-related signals, focusing on digital marketing activities by luxury hotels in Santorini, Greece. Drawing on a case study of the Santorini Earthquake in February 2025—during which the Greek government declared a state of emergency—we use big data analytics, including web traffic metrics, social media interaction and fuzzy cognitive mapping, to analyse behavioural shifts across platforms. The findings indicate that disaster signals trigger increased engagement, altered sentiment and changes in advertising efficiency. This study provides actionable recommendations for tourism destinations and hospitality brands on how to adapt digital strategies during crisis periods. Full article

Background: The aim of the study was to determine the impact of social media on the food purchasing decisions and dietary attitudes of Polish consumers. Methods: The research was conducted using the diagnostic survey method, employing an online questionnaire technique CAWI (Computer Assisted Web Interview). A total of 1099 adults participated in the study, including 54.23% women and 45.77% men. The survey data were analysed using multidimensional discriminant analysis. Results: The study demonstrated that social media significantly affects the purchasing decisions of Polish consumers regarding food products. The study indicated that there is a gender difference in the impact of social media. Women more often use SM to gain knowledge about food products and shape their dietary attitudes, and they are more susceptible to marketing content. Conclusions: It seems necessary to regulate online advertising and eliminate excessive advertising, as this form of publication in the media is the most effective and has a significant impact on the purchase of food products by Polish consumers. Unrestricted access to content and lack of regulation lead to misinformation, which can result in erroneous purchasing choices. Full article

We extended real estate property listings on the online prop-tech platform. On the platform, the images were classified into the specified classes according to quality criteria. The necessary interventions were made by measuring the platform’s appropriateness level and increasing the advertisements’ visual appeal. A dataset of 3000 labeled images was utilized to compare different image classification models, including convolutional neural networks (CNNs), VGG16, residual networks (ResNets), and the LLaVA large language model (LLM). Each model’s performance and benchmark results were measured to identify the most effective method. In addition, the classification pipeline was expanded using image enhancement with contrastive unsupervised representation learning (CURL). This method assessed the impact of improved image quality on classification accuracy and the overall attractiveness of property listings. For each classification model, the performance was evaluated in binary conditions, with and without the application of CURL. The results showed that applying image enhancement with CURL enhances image quality and improves classification performance, particularly in models such as CNN and ResNet. The study results enable a better visual representation of real estate properties, resulting in higher-quality and engaging user listings. They also underscore the importance of combining advanced image processing techniques with classification models to optimize image presentation and categorization in the real estate industry. The extended platform offers information on the role of machine learning models and image enhancement methods in technology for the real estate industry. Also, an alternative solution that can be integrated into intelligent listing systems is proposed in this study to improve user experience and information accuracy. The platform proves that artificial intelligence and machine learning can be integrated for cloud-distributed services, paving the way for future innovations in the real estate sector and intelligent marketplace platforms. Full article

This research investigates the strategic decision related to original content provision and business model selection within the rapidly evolving online video industry. We develop a two-sided market model involving a video platform, users, and advertisers to analyze how the platform balances subscription and advertising revenue while offering original content. This study finds that the amount of original content provided directly influences market equilibrium, affecting the platform’s choice between a purely subscription-based model or a mixed model. The cost of original content production plays a critical role in this decision-making process. High production costs may lead the platform to favor a mixed model, offering less original content to generate both subscription and ad revenue. Lower costs, however, encourage a subscription model with more original content to boost subscribing revenue. Additionally, factors such as network externalities between users and advertisers also impact the business model choice. Importantly, the model shows that allowing free users limited access to original content can expand both subscriber and advertiser engagement, enabling platforms to enhance dual revenue streams without having to sacrifice one for the other. Full article

While speakers of German have adopted many loanwords from other languages throughout history, recent diversification of language use in Germany is mainly driven by the global mobility of English. Previous research has therefore focused on various domains in which English linguistic resources are used, particularly in traditional media and social media communication. Furthermore, many studies on social media communication have also examined English language internet memes more broadly. Despite this plethora of research, little attention has been paid to how English is used in internet memes and reels produced by professional journalists in Germany. Playing a significant role in communication amongst young people, internet memes and reels are used by many German youth media organisations. In particular for youth radio stations in Germany, which have become multimedia outlets, online communication via Instagram is vital for their audience interaction. This paper examines the use of English linguistic resources in a professionally produced Instagram corpus of internet meme and reel captions produced by journalists working for one of the largest youth radio stations in Germany. Data for the analysis of Instagram content were collected as part of the larger ethnographic research project CIDoRA (funded by the European Union). For this project, a mixed methods approach was applied. Methods of data collection and analysis include linguistic ethnography both at the youth radio station and on the station’s Instagram profile page, informal interviews and 20 semi-structured interviews with journalists, and a quantitative and qualitative analysis of 980 meme and reel captions produced for the station’s Instagram profile. Since the youth radio station’s Instagram profile functions as a means of the station’s online self-advertisement, the analysis of this article also draws on a previous study by the researcher. This study analysed possible facilitating factors for the use of catachrestic and non-catachrestic anglicisms in radio station imaging (radio self-advertisement) of six German adult contemporary radio stations. The article therefore includes an analysis of the possible facilitating factors lexical field, brevity of expression, diachronic development of the pragmatic value of lexical items and semantic reasons for the use of English in Instagram content. It thereby explores the differences in anglicism use between these two media formats (radio broadcasting and social media communication) and whether possible facilitating factors for the use of English in adult contemporary radio station imaging are also facilitating factors for the use of English in meme and reel captions produced by the youth radio station. Full article

Systems analysts can be considered a valuable part of organizations, as their responsibilities and contributions concern the improvement of information systems, which constitute an irreplaceable part of organizations. Thus, by exploring the current labor market of systems analysts, researchers can gather valuable knowledge to understand some invaluable societal needs. In this context, the objectives of this study are to investigate the sets of digital skills from the European Skills, Competences, Qualifications, and Occupations (ESCO) taxonomy required by systems analysts in Europe and examine the key characteristics of various relevant sectors. For this purpose, a tool combining topic extraction, machine learning, and statistical analysis is utilized. The outcomes prove that systems analysts may indeed possess different types of digital skills, where 12 distinct topics are discovered, and that the professional, scientific, and technical activities demand the most unique sets of digital skills across 17 sectors. Ultimately, the findings show that the numerous sectors indeed have divergent requirements and should be approached accordingly. Overall, this study can offer valuable guidelines for identifying both the general duties of systems analysts and the specific needs of each sector. Also, the presented tool and methods may provide ideas for exploring different domains associated with content information and distinct groups. Full article

The main objective of this study was to investigate European consumers’ intentions to purchase cosmetics and detergents with green ingredients made from recycled CO₂. Aiming to better understand both moral and practical criteria of consumers’ intentions, a combination of the Values-Beliefs-Norms and the Theory of Planned Behaviour models served as the basis of this study’s theoretical framework. The combination was extended with risk perception about global warming, scepticism and media influence. Online interviews were conducted with stratified samples based on gender and age distributions in France, Germany, Greece and Spain. Structural equation modelling and moderation analyses were employed to analyse the data. The results indicated that consumption intentions are generated by consumers’ biospheric values and a sequence of risk perception, awareness of consequences, and ascription of responsibility while they are directly determined (in declining order) by perceived behavioural control, personal norms, attitudes and subjective norms. Subjective norms indicated additional indirect impacts on consumption intentions through personal norms and ascription of responsibility. Moderation also indicated that the relationship between perceived behavioural control and consumption intentions is stronger in consumers, who are less sceptical towards ecological claims on packaging, while the relationship between personal norms and consumption intentions is stronger in consumers, who are less influenced by advertisements. Theoretical, managerial and social implications were derived from the results. Full article

Background/Objectives: This study investigated whether exposure to various types of information online can influence adults aged 40 and above in their likelihood to purchase hearing aids (HAs). Specifically, it examined the effects of price anchoring, using high or low HA prices in advertisements, and attribute framing, using product descriptions that highlighted lifestyle appeal or technological capabilities. Methods: In a 2 × 2 experimental design, 271 participants browsed a website simulating an online search for hearing health information. Participants then rated their likelihood of purchasing three fictitious HAs as well as their likelihood of not purchasing any device. Results: Two-way ANCOVAs indicated no significant main effects of anchoring or framing on purchase likelihood for the fictitious devices (covariates included self-rated hearing ability, trust in online health information, and HA knowledge and importance). No significant interaction effects emerged. However, exploratory analyses revealed significant anchoring effects for two of the three devices among participants with below-median self-rated hearing. Additionally, self-rated knowledge was a significant covariate in the model for all devices (p < 0.001), positively correlating with purchase likelihood. Participants with above-median self-rated knowledge showed significantly higher purchase likelihood for all devices (p < 0.001, d ≥ 0.572 for all comparisons), while those with below-median knowledge displayed a significant anchoring effect for two outcomes. Conclusions: Enhanced HA knowledge may increase HA purchase likelihood and reduce the potential anchoring effects of online advertising. Further research is needed to determine the impact of exposure to high or low prices on HA purchase decisions, especially among those with poorer hearing. Full article