Adapting the WHO MPOWER framework for E-cigarettes: Qualitative insights from South Korea.

Digital marketing and the behavioral intention to use learning management systems.

Does brand anthropomorphism matter? Impact on brand loyalty and consumer decision-making

Influence of technological integration and design aesthetics on consumer engagement in digital marketing campaigns

Digital market adoption by underserved MSMEs in developing countries: Mediation and moderation by self-efficacy and trust

Improving representativeness in trial recruitment: A data-driven approach.

The global gig economy has witnessed exponential growth, contributing significantly to the digital labor market. However, traditional centralized freelancing platforms (e.g., Upwork, Fiverr) are plagued by high intermediary fees (up to 20%), delayed settlements, and opaque dispute resolution mechanisms. This paper presents a comprehensive review of blockchain based alternatives, analyzing the efficacy of Distributed Ledger Technology (DLT) in mitigating these centralization bottlenecks. We critically examine existing smart contract based escrow mechanisms and identify key challenges in scalability and user adoption. Based on this review, we propose “Delance,” a hybrid Web3 architecture that utilizes the Polygon network to minimize gas fees while ensuring instant, trustless settlements. Comparative analysis demonstrates that the proposed architecture reduces transaction costs by 98% compared to traditional Web2 platforms, validating the feasibility of a decentralized freelance ecosystem.

Tourism management has become one of the most important contributors to economic development in many regions around the world. In the Kurdistan Region of Iraq, tourism has experienced significant growth due to the region’s natural landscapes, historical attractions, cultural diversity, and increasing investment in tourism infrastructure. The purpose of this quantitative research study is to examine the modern dimensions of tourism management and their role in promoting economic progress in the Kurdistan Region. The study investigates how strategic tourism planning, digital tourism marketing, tourism infrastructure, service quality, and government support influence economic development indicators such as employment generation, investment growth, business expansion, and regional income improvement. A quantitative research design was adopted using a structured questionnaire distributed among tourism sector employees, hotel managers, travel agencies, tourism officials, and visitors in the Kurdistan Region. A total of 250 questionnaires were collected and analyzed using Statistical Package for Social Sciences (SPSS). Descriptive statistics, reliability analysis, Pearson correlation, and multiple regression analysis were employed to examine relationships between tourism management dimensions and economic progress. The findings revealed strong positive relationships between modern tourism management practices and economic progress.

Search Engine Optimization (SEO) has become a cornerstone of digital marketing strategy in the contemporary business environment. This study investigates the impact of SEO on website traffic and lead generation, drawing on primary data collected from 200 digital marketing professionals in India. The research evaluates five key dimensions: SEO impact on website traffic, effectiveness of SEO techniques, role of content quality and keyword strategy, SEO contribution to lead generation and conversion, and the influence of backlinks and domain authority. Employing quantitative research methods including descriptive statistics, Pearson correlation analysis, multiple linear regression, independent samples t-test, and one-way ANOVA, the study reveals strong and statistically significant relationships among all SEO dimensions. Regression analysis demonstrates that content strategy is the most influential predictor of overall SEO performance (β = 0.359), followed by backlink authority and SEO effectiveness. The model explains 80.3% of the variance in overall SEO performance (R² = 0.803). Demographic variables such as gender and experience level do not significantly influence SEO perceptions, indicating consensus across respondent groups. The findings confirm that SEO is a highly effective, cost-efficient, and long-term strategy for driving organic traffic and generating quality leads. Practical recommendations for businesses and digital marketers are discussed. Keywords: Search Engine Optimization, SEO, Website Traffic, Lead Generation, Digital Marketing, Content Strategy, Backlinks, Organic Search, Keyword Optimization, Conversion Rate

ABSTRACT The digital transformation of marketing in the hotel industry has altered how customer data is gathered, processed, and used for personalization and to change customer experience. The adoption of cloud computing has enabled a key enabler of such digital marketing strategies by suggesting the scalability, flexibility, and cost-efficiency needed. However, the risen use of cloud computing has brought up issues linked to customer data security, privacy, and compliance. As a result, the management of effective customer data protection is a significant strategic focus for hotels operating in fiercely competitive and data-driven markets. This research investigates the effects of advanced security governance, operational security, and security knowledge and skills in developing the effectiveness of customer data protection in the context of digital marketing over the cloud. It further investigates IT security’s moderate role in increasing these relationships. Through structural equation modeling (SEM) analysis of data gathered from IT and marketing experts in the hotel industry, the results propose that all elements play a significant role in ornamental data protection directly and indirectly (via IT security), underscoring the latter’s importance.

Online food purchasing lacks the direct sensory experience of physical stores, making it difficult for consumers to assess food quality and value. This study investigated how visual sensory cues and mental imagery elicited by food photographs on major Malaysian delivery platforms influence perceptions of food quality, value, satisfaction, and purchasing behavior. Drawing on the Stimulus-Organism-Response (S-O-R) model, a quantitative survey was administered to 354 Klang Valley residents with online food ordering experience, using Google Forms and QR code distribution. They selected a non-probability convenience sampling technique. Structural equation modeling (PLS-SEM) was used to test the proposed relationships. Findings revealed that sensory cues, especially vivid food images, significantly stimulated mental imagery, enabling consumers to virtually evaluate product attributes and compensating for the lack of physical interaction. Mental imagery positively affected perceived quality, value, and satisfaction. This study also found that satisfaction was a strong predictor of purchase behavior. These results underlined the critical role of high-quality visuals and imagery in digital food marketing strategies. The study offered theoretical and practical insights for food brands and platform operators, demonstrating how enhancing visual content can foster favorable consumer perceptions and drive purchase decisions in online food delivery contexts.

The article provides a comprehensive theoretical substantiation and analysis of the practical aspects of implementing artificial intelligence (AI) and educational simulators within the higher education system. The relevance of the study is driven by the urgent need to bridge the gap between traditional academic knowledge and the rapidly evolving requirements of the global digital labor market. The author explores the didactic potential of AI-driven simulators as sophisticated tools for modeling real-world professional scenarios, offering a risk-free environment for the systematic development of students' hard skills and decision-making abilities. The research identifies the critical role of mobile applications in constructing flexible educational trajectories and ensuring seamless, ubiquitous access to interactive learning content. A comparative analysis between traditional teaching models and innovative simulation-based approaches is presented, highlighting the advantages of automated feedback and adaptive learning paths. The study details the architectural components of an intelligent educational ecosystem, including cognitive simulators, analytical modules based on Big Data, and mobile interaction platforms. Significant emphasis is placed on the transformation of the educator's role, shifting from a primary source of information to an architect and moderator of a high-tech learning space. This transition necessitates the continuous development of teachers' digital competencies to manage AI-integrated processes effectively. The findings prove that the synergy of artificial intelligence, mobile technologies, and simulation modeling fosters deep personalization of the learning process. This integration not only enhances student engagement through gamification and SMART-structured tasks but also significantly improves the overall quality and efficiency of professional training for future specialists in various fields, from information technology to physical education and sports. The study concludes that the future of higher education lies in the harmonious balance between human pedagogical expertise and advanced algorithmic support.

This paper explores online impulse buying behavior (IBB) triggers in online retail setting in terms of its antecedents (sales promotion (SP), web quality (WQ), online shopping behavior (OSB) and fashion consciousness (FC) as well as openness personality (OP) as a moderating characteristic. A structured survey was used to gather data of 400 respondents. The analysis was done using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings established by SP, WQ, OSB and FC have significant effects on OSBFC which in turn triggers IBB. There were statistically significant mediation and moderation effects. The model accounted for 58.7% variance in IBB, which can have significant implications for the digital marketers and the e-commerce practitioners.

This community service activity aims to improve the human resource capacity of the Bantaragung Majalengka Tourism Village managers through training in creative content and digital marketing campaign strategies. The method used was Participatory Action Research (PAR), which actively involved participants through the stages of planning, action, observation, and reflection. The activities included training in digital content creation, social media management, and designing digital campaigns based on hands-on practice. Evaluation results showed a significant increase in participant understanding, with an average pre-test score of 58.0 increasing to 80.4 in the post-test, an increase of 38.6%. In addition, participants were able to produce more creative content and began implementing digital marketing strategies independently. The impact of implementation was seen in the increase in the tourism village's social media activity, including the number of posts, user interactions, and follower growth.

This study aimed to quantify the impact of adolescents' exposure to unhealthy food marketing in real-world digital environments. We conducted a single-blinded randomized field experiment including 121 Australian adolescents aged 16-17. A latent class analysis was used to identify personas, and participants were randomized (1:1) to an intervention or control group. Using retargeting pixels, the intervention group was exposed to advertisements for a fictitious sugar-sweetened beverage "Clu" embedded in their feed for 2 weeks. The control group was not exposed to Clu advertisements. An exit survey collected data on purchase intention for Clu. Exposure effect on purchase intention was estimated using logistic regression, reported as a risk ratio. An intention to purchase Clu was reported by 26.2% of participants (n = 16) in the control and 71.6% in the intervention group (n = 43). Participants in the intervention group were 2.73 times more likely to report intention to purchase Clu than those in the control (RR = 2.73; 95% CI: 1.74-4.28). Social media advertisements for sugar-sweetened beverages significantly influence adolescents' purchase intentions of the beverages, highlighting digital advertising as a modifiable commercial determinant of dietary risks. These findings underscore the need for policy interventions that address unhealthy food digital marketing to reduce obesity-related behaviors among adolescents.

Impulsive purchasing behavior has become a significant focus in e-commerce research owing to the swift growth of digital marketplaces and technology-fueled consuming settings. This study seeks to systematically delineate and synthesize global research trends regarding impulsive buying behavior within the realm of e-commerce using extensive bibliometric analysis. The study examines 393 peer-reviewed papers and reviews from Scopus-indexed publications between 2000 and 2025, employing recognized bibliometric methodologies such as performance analysis, citation analysis, co-authorship analysis, co-citation analysis, and keyword co-occurrence mapping. Visualization technologies like VOS viewer are utilized to elucidate the intellectual framework, thematic progression, and collaborative dynamics within the discipline. The results demonstrate a distinct historical transition from initial technology-focused study to interdisciplinary studies that incorporate consumer psychology, digital marketing, social commerce, and advanced technologies like artificial intelligence and live-stream commerce. The findings delineate key authors, institutions, nations, and journals, emphasizing the preeminent influence of the United States and China, as well as the significance of high-impact journals in information systems and consumer behavior. The thematic analysis indicates an increasing academic focus on the emotional, experiential, and social aspects of impulsive purchasing, as well as rising issues pertaining to consumer welfare and ethical platform design. This study presents a systematic assessment of the knowledge domain, identifies research deficiencies, and gives significant insights to inform future academic research, managerial decisions, and policy formulation in digital consuming situations.

Social media marketing emerged as a popular and effective strategy for companies to promote their products due to the rapid development of digital technology. This approach of marketing has been utilising more by businesses as it offers target audiences more choices. Social Media Marketing or SMM use the power of social media influencers in building and maintaining a strong relationship with the audience. Influencer marketing is a collaboration between a brand and an online personality, known as Social Media Influencer or SMI who will endorse and promote products, services, ideas or brands to their followers. Technological advancements in the form of artificial intelligence (AI) is also a recent trend in influencer marketing which is used in the form of chatbots and virtual influencers. These digital personalities are used in influencer marketing to support brands and increase their marketing efforts. For the brands which are constantly looking for innovative ways to engage with their target audience, introduction of chatbots and virtual influencers has opened new possibilities. This research focuses on the role of chatbots and virtual influencers in influencer marketing and examines how they impact consumer engagement, trust and brand perception. For the purpose of this study, qualitative research method is adopted to examine consumer attitude towards chatbots and virtual influencers. Researchers collected data from reviewing existing literature and semi-structured interviews to understand consumer perception. The study also explains the methods such as creating personal experience and automated interactions through which the brands strengthen their online presence. This study also provides valuable information on the effectiveness of chatbots and virtual influencers in influencer marketing which adds to the expanding knowledge of digital marketing. It also stresses on the opportunities and challenges to integrate these technological advancements in the marketing efforts of the brands. The study provides recommendations for brands to strengthen customer engagement by maintaining trust and authenticity.

This study examines the relationship between digital promotion, customer engagement, and sales performance in the telecommunications industry, with empirical evidence drawn from the Federal Capital Territory (FCT), Abuja, Nigeria, situated within the broader context of global telecommunications trends. The rapid expansion of digital technologies has transformed marketing practices in the telecom sector, shifting emphasis from traditional promotional methods toward data-driven, interactive, and personalized digital engagement strategies. Despite this transformation, there remains limited empirical evidence on how digital promotional activities translate into measurable sales performance outcomes in developing economies such as Nigeria. The study adopts a quantitative research design using survey and secondary data collected from selected telecommunications operators and customers within FCT Abuja. The analysis employs structural equation modeling (SEM) to examine the direct and indirect relationships among digital promotion, customer engagement, and sales performance. Digital promotion is operationalized through social media campaigns, SMS marketing, mobile application advertising, and online promotional offers, while customer engagement is measured through interaction frequency, brand participation, and loyalty indicators. Sales performance is assessed using subscriber acquisition, revenue growth, and customer retention metrics. Findings indicate that digital promotion has a significant positive effect on both customer engagement and sales performance. Furthermore, customer engagement is found to partially mediate the relationship between digital promotion and sales performance, suggesting that promotional effectiveness is enhanced when customers actively interact with telecom brands. The results also reveal that the effectiveness of digital promotion in Abuja reflects global telecommunications trends, particularly the increasing reliance on personalized marketing, real-time customer interaction, and data analytics-driven decision-making. The study contributes to the literature by integrating customer engagement as a mediating construct in the promotion–performance relationship and by providing empirical evidence from a developing-country context. It offers practical implications for telecommunications firms seeking to optimize digital marketing strategies and improve competitive advantage in an increasingly digitized global marketplace.

Digital marketing and sustainability awareness in Saudi higher education: the roles of green student engagement and institutional support

The success of any organization is contingent upon the behavior and incidents of its customers. Moreover, consumer purchasing patterns are essential in ensuring the fast expansion of e-commerce sites, as they will aid in retention and targeted advertising. The study examines behavioral patterns and predicts potential churners using the E-commerce Customer Churn Prediction dataset. Some models, such as the Logistic Regression (LR) and Generative Adversarial Network (GAN), Deep Neural Network (DNN), and the proposed CNN-LSTM model, are applied and tested with the help of some of the main performance indicators, such as accuracy, precision, recall, and F1-score. The dataset is preprocessed through missing value are fixed, one-hot encoding is done, the data are normalized, and the balancing of the classes is performed with the help of SMOTE in order to increase the reliability of the models. The experimental outcomes indicate that the CNN-LSTM model is better than other models, with an accuracy of 98.56, a precision of 98.25, a recall of 99.87, and the F1score of 99.56, which suggests that it is highly effective in impressing the complicated patterns of consumer behavior. The outcomes reveal the usefulness of DL methods in projecting customer churn and aiding data-driven decision-making in e-commerce websites of digital fashion.