Enhance User Engagement Research Articles

UNRAVELLING THE DETERMINANTS OF SOCIAL MEDIA PAYMENT PLATFORM (SMPP) USAGE: A QUALITATIVE STUDY ON USER INTENTIONS AND ADOPTION

Lately, social media companies worldwide have introduced payment features on their social media platforms. This has given social media users the option to make payments to their near and dear ones without changing the platform while engaged in chatting. The adoption of Social Media Payment Platforms (SMPP) varies across user groups and is influenced by socio-demographic characteristics, convenience, and perceived risk. Understanding these factors is essential for enhancing user engagement and trust, thereby addressing the gaps in current SMPP adoption research. The purpose of this study is to ascertain the behavioural intention and perception level of users toward Social Media Payment Platforms (SMPP) adoption and to identify the factors which motivate and inhibit from using social payment apps. To understand the intention of the users to behave and adopt SMPP, we conducted in-depth structured interviews. Qualitative analysis was used to analyse the data, using pre-defined categories (deductive) and code emerging from the respondent discussions (inductively) to identify the relevant influencing factors. Through data analysis, we identified three key themes that categorised user behaviour: socio-demographic, convivence and vulnerability to risks, which is further divided into several sub-themes such as age, gender, education, occupation under socio-demographic, while perceived usefulness (PU) and perceived ease of use (PEOU) comes under the theme of convivence and lastly, under Vulnerability of risk includes privacy, security and platform features. The findings of the study can be validated and explored in future research, which will provide a clear understanding of identifying factors that influence SMPP adoption and behaviour intention.

Enhancing user engagement and loyalty in online travel agents: a gamification approach

Purpose This study aims to investigate the effects of gamification features on brand engagement dimensions in online travel agents (OTAs), specifically brand awareness and loyalty. Design/methodology/approach The proposed model is empirically evaluated through an online survey of 406 Indonesian OTA users. Partial least squares structural equation modeling analysis was used to assess the model. Findings The findings reveal that gamification boosts emotional and social brand engagement, while achievement improves cognitive brand engagement. Cognitive brand engagement only affects brand loyalty, excluding brand awareness; however, emotional and social brand engagement substantially impact brand awareness and loyalty. Originality/value This study addresses the gap in the limited empirical studies on gamification in the tourism and hospitality industries, with a particular focus on OTAs.

ShinySperm: navigating the sperm proteome landscape.

Context Integrated omics studies hold a crucial role in improving our understanding of reproductive biology. However, the complex datasets so generated are often only accessible via supplementary data files, which lack the capacity for interactive features to allow users to readily interrogate and visualise data of interest. Aims The intent of this technical note was to develop an interactive web-based application that enables detailed interrogation of a representative sperm proteome, facilitating a deeper understanding of the proteins identified, their relative abundance, classifications, functions, and associated phenotypes. Methods We developed a Shiny web application, ShinySperm (https://reproproteomics.shinyapps.io/ShinySperm/ ), utilising R and several complementary libraries for data manipulation (dplyr), interactive tables (DT), and visualisation (ggplot2, plotly). ShinySperm features a responsive user interface, dynamic filtering options, interactive charts, and data export capabilities. Key results ShinySperm allows users to interactively search, filter, and visualise sperm proteomics data based on key features (e.g. protein classification, sperm cell domain, presence, or absence at different maturation stages). This application responds live to filtering options and enables the generation of interactive plots and tables, thus enhancing user engagement and understanding of the data. Conclusions ShinySperm provides a robust platform for the dynamic exploration of epididymal sperm proteome data. It significantly improves accessibility and interpretability of complex datasets, allowing for effective data-driven insights. Implications This technical note highlights the potential of interactive web applications in reproductive biology and provides a plug and play script for the field to produce applications for meaningful researcher interaction with complex omic datasets.

Reshaping Financial Experience: An Optimization Strategy Study on Short Video in the Promotion of Digital Financial Products

In the increasingly competitive field of digital finance, financial institutions can better establish connections with target customer groups through carefully designed short video promotions. This study explores the role and optimization path of short videos in promoting digital financial products from the perspective of short videos. By analyzing the user behavior and interaction patterns of short video platforms, combined with the characteristics of digital financial products, targeted promotion strategies have been proposed. These strategies can not only help financial institutions more effectively reach potential customers, but also enhance user engagement and loyalty.

Predicting Online Gaming Behaviour Using Machine Learning Techniques

Understanding player behaviour in online gaming is essential for enhancing user engagement and retention. This study utilizes a dataset from Kaggle, capturing a wide range of player demographics and in-game metrics to predict player engagement levels categorized as 'High,' 'Medium,' or 'Low.' The dataset includes features such as age, gender, location, game genre, playtime, in-game purchases, game difficulty, session frequency, session duration, player level, and achievements. The research employs a Gaussian Naive Bayes model, with data pre-processing steps including feature selection, categorical data encoding, and scaling of numerical features. The dataset is split into training (80%) and testing (20%) sets, and a 5-fold cross-validation is used to ensure model robustness. The model's performance is evaluated using accuracy, precision, recall, and F1-score. The results show consistent performance across different folds, with an average accuracy of 84.27%, precision of 85.59%, recall of 84.27%, and F1-score of 83.98%. These findings indicate that the Gaussian Naive Bayes model can reliably predict player engagement levels, identifying significant predictors such as session frequency and in-game purchases. The study contributes to game analytics by providing a predictive model that can help game developers and marketers design more engaging gaming experiences. Future research should incorporate a broader range of features, including psychological and social factors, and explore other machine learning algorithms to enhance predictive accuracy. This study's insights are valuable for developing strategies to improve player retention and satisfaction in the gaming industry.

Exploring the Intersection of Subliminal Perception and Digital Marketing

Abstract: Subliminal refers to stimuli that operate below the threshold of conscious perception. Subliminal advertisements target the subconscious, where consumers may not consciously assess the content. However, their impact becomes apparent through indirect observations, such as the influence on emotions, the effect on cognitive processes, the ability of consumers to consciously evaluate these ads, the level of excitement and engagement with characters portrayed in subliminal ads, and various other aspects. This research delves into the intersection of subliminal perception and digital marketing, seeking to unravel the subtle influences that impact consumer behaviour in the digital realm. By employing a comprehensive methodology that includes surveys, content analysis, and hypothesis testing, the study aims to explore how individuals perceive and respond to subliminal cues embedded in digital marketing content. Ethical considerations guide the research process to ensure transparency and consumer well-being. A sample size of 126 participants, encompassing both male and female youths aged 18-30, was selected from diverse professional and non-professional backgrounds. The findings contribute valuable insights into the complex interplay between subliminal perception and digital marketing strategies, offering implications for marketers aiming to enhance user engagement, brand perception, and overall effectiveness in the online landscape.

Investigating the Factors Influencing User Loyalty, Purchase Intention, and Word-of-Mouth in Virtual Reality

Abstract This study investigates the determinants of loyalty, purchase intention, and word-of-mouth (WOM) recommendations in the context of virtual reality (VR) technology, focusing on sensory design components such as visual (color, navigation design, aesthetics, shape, and product design), tactile (touch), and auditory (audio) elements. Employing partial least squares structural equation modeling, data from individuals experienced with VR headsets were analyzed to explore how these sensory aspects influence user behavior. Contrary to expectations, color did not significantly influence attitude or satisfaction. Navigation design significantly impacted both user attitude and satisfaction, highlighting its importance in the VR experience. While aesthetics were found to positively affect user attitude, they did not significantly influence satisfaction. Interestingly, the shape of VR devices influenced satisfaction but not attitude. The product design of VR devices significantly affected both attitude and satisfaction, but audio factors did not significantly impact either. The results indicate that user attitude significantly influences loyalty, purchase intention, and WOM, as does user satisfaction. This reveals the critical role of design and sensory elements in shaping user experiences and preferences within VR environments, offering insights for developers and marketers aiming to enhance user engagement and loyalty.

Regulatory Fit to Enhance User Engagement with an App Promoting Healthy and Sustainable Eating. An Experimental Study to Match Regulatory Concern and Anticipated Emotions

Regulatory Fit to Enhance User Engagement with an App Promoting Healthy and Sustainable Eating. An Experimental Study to Match Regulatory Concern and Anticipated Emotions

Research Paper on Artificial Intelligence

Artificial Intelligence (AI) has emerged as a transformative force across various sectors, revolutionizing processes, enhancing efficiency, and redefining innovation. This research paper delves into the multifaceted landscape of AI, focusing on its applications, knowledge representation, and implications for innovation. The paper begins by exploring the diverse applications of AI across healthcare, gaming, finance, data security, social media, robotics, and e-commerce. In healthcare, AI aids in diagnosis and patient care, while in gaming, it enables strategic game play and enhances user experience. The finance sector leverages AI for automation, analytics, and algorithmic trading, improving decision-making and customer service. AI also plays a vital role in ensuring data security through advanced detection systems, manages vast social media data for enhanced user engagement, and drives innovation in robotics and e-commerce. Moving forward, the paper delves into the realm of expert systems and knowledge representation, elucidating the role of AI in simulating human expertise and modeling complex information structures. It discusses various aspects of knowledge representation, such as propositional knowledge representation, image retrieval, functional relationships between objects, and class representation formalism, highlighting their significance in developing intelligent systems. Furthermore, the paper examines the integration of AI in maintenance practices, both for tangible systems like engineering workshops and intangible products like data extraction wrappers. It underscores the importance of AI in optimizing operational efficiency, reducing downtime, and ensuring continuous data extraction. Lastly, the paper explores the concept of deep learning as a general- purpose invention, discussing its potential implications for innovation, management, institutions, and policy. It addresses key issues such as the management and organization of innovation, intellectual property rights, competition policy, and the cumulative knowledge production facilitated by deep learning. In conclusion, this research paper provides a comprehensive overview of AI's transformative potential, emphasizing the need for further research and analysis to fully comprehend its impact on society, economy, and innovation.

A Chatbot-Based Version of the World Health Organization-Validated Self-Help Plus Intervention for Stress Management: Co-Design and Usability Testing.

Advancements in technology offer new opportunities to support vulnerable populations, such as pregnant women and women diagnosed with breast cancer, during physiologically and psychologically stressful periods. This study aims to adapt and co-design the World Health Organization's Self-Help Plus intervention into a mobile health intervention for these target groups. On the basis of the Obesity-Related Behavioral Intervention Trials and Center for eHealth Research and Disease Management models, low-fidelity and high-fidelity prototypes were developed. Prototypes were evaluated by 13 domain experts from diverse sectors and 15 participants from the target groups to assess usability, attractiveness, and functionality through semantic differential scales, the User Version of the Mobile Application Rating Scale questionnaire, and semistructured interviews. Feedback from participants indicated positive perceptions of the mobile health intervention, highlighting its ease of use, appropriate language, and attractive multimedia content. Areas identified for improvement included enhancing user engagement through reminders, monitoring features, and increased personalization. The quality of the content and adherence to initial protocols were positively evaluated. This research provides valuable insights for future studies aiming to enhance the usability, efficacy, and effectiveness of the app, suggesting the potential role of a chatbot-delivered Self-Help Plus intervention as a supportive tool for pregnant women and women with a breast cancer diagnosis.

Enhancing software engineering with visual design and multimedia: An empirical and theoretical exploration

This article delves into the critical role of visual design and multimedia integration within software engineering, emphasizing their significance in enhancing user engagement, comprehension, and collaboration among stakeholders. Through a comprehensive analysis of theoretical frameworks, quantitative research findings, and practical applications, this study elucidates the benefits and challenges associated with embedding visual and multimedia elements in software systems. It presents empirical evidence from controlled studies and case analyses to demonstrate the tangible improvements in software usability, educational efficacy, and project management efficiency. Moreover, the article explores future directions, highlighting emerging technologies and methodologies that promise to further revolutionize the integration of visual design in software engineering. The findings underscore the pivotal role of visual and multimedia elements in bridging communication gaps, fostering collaborative environments, and enhancing the overall software development process.

Usability and Preliminary Efficacy of an Adaptive Supportive Care System for Patients With Cancer: Pilot Randomized Controlled Trial.

Using an iterative user-centered design process, our team developed a patient-centered adaptive supportive care system, PatientCareAnywhere, that provides comprehensive biopsychosocial screening and supportive cancer care to patients across the continuum of care adaptively. The overarching goal of PatientCareAnywhere is to improve health-related quality of life (HRQOL) and self-efficacy of patients with cancer by empowering them with self-management skills and bringing cancer care support directly to them at home. Such support is adaptive to the patient's needs and health status and coordinated across multiple sources in the forms of referrals, education, engagement of community resources, and secure social communication. This study aims to assess the usability of the new web-based PatientCareAnywhere system and examine the preliminary efficacy of PatientCareAnywhere to improve patient-reported outcomes compared with usual care. For phase 1, usability testing participants included patients with cancer (n=4) and caregivers (n=7) who evaluated the software prototype and provided qualitative (eg, interviews) and quantitative (eg, System Usability Scale) feedback. For phase 2, participants in the 3-month pilot randomized controlled trial were randomized to receive the PatientCareAnywhere intervention (n=36) or usual care control condition (n=36). HRQOL and cancer-relevant self-efficacy were assessed at baseline (preintervention assessment) and 12 weeks from baseline (postintervention assessment); mean differences between pre- and postintervention scores were compared between the 2 groups. Participants were highly satisfied with the prototype and reported above-average acceptable usability, with a mean System Usability Scale score of 84.09 (SD 10.02). Qualitative data supported the overall usability and perceived usefulness of the intervention, with a few design features (eg, "help request" function) added based on participant feedback. With regard to the randomized controlled trial, patients in the intervention group reported significant improvements in HRQOL from pre- to postintervention scores (mean difference 6.08, SD 15.26) compared with the control group (mean difference -2.95, SD 10.63; P=.01). In contrast, there was no significant between-group difference in self-efficacy (P=.09). Overall, PatientCareAnywhere represents a user-friendly, functional, and acceptable supportive care intervention with preliminary efficacy to improve HRQOL among patients diagnosed with cancer. Future studies are needed to further establish the efficacy of PatientCareAnywhere as well as explore strategies to enhance user engagement and investigate the optimal intensity, frequency, and use of the intervention to improve patient outcomes. ClinicalTrials.gov NCT02408406; https://clinicaltrials.gov/study/NCT02408406.

Environmental Insights: Democratizing access to ambient air pollution data and predictive analytics with an open-source Python package

Ambient air pollution is a pervasive issue with wide-ranging effects on human health, ecosystem vitality, and economic structures. Utilizing data on ambient air pollution concentrations, researchers can perform comprehensive analyses to uncover the multifaceted impacts of air pollution across society. To this end, we introduce Environmental Insights, an open-source Python package designed to democratize access to air pollution concentration data. This tool enables users to easily retrieve historical air pollution data and employ a Machine Learning model for forecasting potential future conditions. Moreover, Environmental Insights includes a suite of tools aimed at facilitating the dissemination of analytical findings and enhancing user engagement through dynamic visualizations. This comprehensive approach ensures that the package caters to the diverse needs of individuals looking to explore and understand air pollution trends and their implications. Code repository clickable linkEnvironmental Insights Github Home Page.

Dealing with Diversity in Digital Psychological Interventions for Young People: A Structured Review

AbstractIn recent years, despite significant progress in digital psychological interventions (DPIs), the prevalence of psychological issues among young adults remains a concern. While research on the feasibility and effectiveness of DPIs is extensive, there's a growing recognition of the need for a sociotechnical approach to enhance user engagement. This review aims to highlight the importance of integrating diversity, especially sociodemographic characteristics, into DPI design and implementation.The review meticulously examined literature from six academic databases focused on DPIs tailored for users aged 12 to 26, spanning the period between 2009 and 2019. The data extraction process specifically targeted biosocial factors such as gender and ethnicity, as well as sociocultural elements like remoteness and labor force status among users. Among the initial pool of 879 articles, a refined selection of 25 underwent detailed analysis. Intriguingly, 14 of these studies did not treat sociodemographic factors as independent variables, leaving only 11 that did. Notably, gender and ethnicity emerged as the most frequently studied factors, with remoteness and labor force considerations receiving comparatively less attention.Despite the acknowledged importance of user engagement in DPI effectiveness, the review highlights a critical gap: insufficient consideration of young adults' sociodemographic characteristics in intervention design and implementation. Therefore, the findings strongly support further mixed-method studies to fully understand the complex social factors influencing user engagement with DPIs. Closing this gap will undoubtedly refine and optimize DPIs to better meet the diverse needs of young adults dealing with psychological challenges.

ELEVATING HOSPITALITY THROUGH DIGITAL INNOVATION

Abstract: In response to the burgeoning demand for elevated hospitality experiences in Nagpur’s luxury event venues, Rama Celebration has embarked on a transformative digital journey aimed at redefining guest experiences and operational excellence. This research paper delves into Rama Celebration’s innovative approach to hospitality through the integration of cutting-edge digital technologies. The centerpiece of this endeavor is Rama Celebration’s web-based platform, meticulously crafted with advanced technologies such as Node.js, Tailwind CSS, and JavaScript. This platform represents a quantum leap in event planning and management, offering an intuitive interface that simplifies the complexities of event booking, venue exploration, and access to premium amenities. Through an exhaustive analysis of the platform’s development process, this paper sheds light on its pivotal role in enhancing guest satisfaction, optimizing resource allocation, and fostering business growth. The platform’s user-centric design philosophy prioritizes seamless navigation, aesthetically pleasing layouts, and interactive elements, thereby enhancing user engagement and satisfaction. Leveraging modern web technologies, the platform ensures scalability, responsiveness, and cross-device compatibility, catering to the diverse needs and preferences of users.Moreover, the platform’s robust architecture, fortified by Node.js server-side scripting and MongoDB database integration, ensures reliability, security, and efficient data management. Advanced features such as real-time availability updates, map-based visualization, and personalized recommendations further enrich the user experience, empowering guests to make informed decisions effortlessly. By embracing digital innovations, Rama Celebration aims to set a new benchmark for excellence in the hospitality industry, spearheading a paradigm shift in luxury event venue management.Looking ahead, the platform holds immense potential for future enhancements and innovations. Integration with mobile applications, augmented reality (AR) features for virtual venue tours, and predictive analytics for personalized guest experiences are among the key areas of focus for future development. Additionally, continuous evaluation, user feedback mechanisms, and performance optimization will be instrumental in ensuring the platform’s sustained relevance and competitiveness in the dynamic hospitality landscape. Keywords: Rama Celebration, Node.js, Tailwind CSS, JavaScript, Event Venue, Digital Transformation, Guest Experience, Operational Efficiency.

Personalized Recommendation Research Based on Logistic Regression Algorithm for Amazon Product Reviews

<p class="MsoNormal" align="justify"><span style="font-family: Times New Roman;">This study explores personalized recommendation strategies within Amazon's product review system using the Logistic Regression algorithm. By analyzing user behavior and review data, a predictive model was developed to forecast user preferences for specific products. The research employed extensive real-world data and validated the model's effectiveness and accuracy through empirical analysis. Findings indicate that the proposed personalized recommendation system significantly enhances user experience and increases product sales. The study contributes an effective recommendation algorithm for e-commerce platforms, offering practical implications for enhancing user engagement and optimizing marketing strategies in competitive markets.</span></p>

Enhancing user engagement and satisfaction through personalized news recommendation systems

Personalized news recommendation systems have emerged as essential tools in addressing information overload by tailoring news content to individual user preferences. This paper provides a comprehensive overview of the advanced techniques employed in these systems, their impacts on user engagement, and the ethical considerations surrounding their development and implementation. We delve into the intricacies of data collection, processing, and user profiling, highlighting the methodologies and challenges inherent in each stage. Additionally, we explore advanced algorithmic foundations, including collaborative filtering, content-based filtering, and hybrid methods, elucidating their strengths and limitations. Furthermore, we examine the dynamics of user engagement within personalized news recommendation systems, analyzing key metrics and the role of user feedback in refining recommendation algorithms. Finally, we address privacy concerns, data sparsity issues, and biases, proposing solutions to mitigate ethical challenges and uphold user trust and fairness. This paper serves as a comprehensive guide for researchers, practitioners, and policymakers navigating the complexities of personalized news recommendation systems.

Artificial Intelligence for Media: Opportunities or Threats

The emergence of artificial intelligence (AI) has ushered in an era of unprecedented possibilities and, at the same time, poses significant threats in the media landscape. As a potent tool, AI can streamline operations, offering innovative solutions like content personalization, predictive analytics, and augmented reality experiences that can enhance user engagement and boost the media industry’s economic viability. These opportunities allow for a more immersive and personalized user experience, leveraging data to create content that is finely tuned to individual preferences and trends. However, the integration of AI in media does not come without its challenges. The threat of deep fakes and the dissemination of misinformation stand as substantial concerns, with AI technologies facilitating the creation of highly convincing fake content that can manipulate perceptions and sow discord. Moreover, the autonomy given to AI systems can potentially lead to job displacements and raise ethical concerns regarding privacy and data security. Despite these threats, when wielded responsibly and ethically, AI can usher in a new golden age for media characterized by creativity, efficiency, and innovation. As the media industry stands at this crossroads, it must navigate the fine balance between leveraging AI’s opportunities and mitigating its potential threats, fostering a landscape that upholds truth, ethics, and human value at its core. It is imperative for stakeholders to collaborate, devising strategies and regulatory frameworks to ensure AI serves as a force for good, steering media towards a future that embodies progress and inclusivity.

Sync Alert Notice Board

The SyncAlert Notice Board project represents a significant advancement in communication technology, leveraging a sophisticated integration of hardware components to create a versatile communication hub. At its core, the project features a 45x6 LED matrix, enabling vivid and customizable display capabilities for messages and notifications. This matrix is complemented by an RTC (Real-Time Clock) module, ensuring accurate timekeeping and scheduling functionalities essential for managing events and deadlines effectively. In addition to visual communication, the project incorporates an MP3 module, adding an auditory dimension to message delivery and enhancing user engagement. The integration of a Bluetooth HC05 module further enhances the project's utility by enabling seamless wireless transmission of data, allowing users to update the notice board remotely and in real time. This combination of features transforms the SyncAlert Notice Board into a dynamic and interactive communication tool suitable for a wide range of environments, from educational institutions to corporate offices. By addressing the specific needs of users for efficient information dissemination and scheduling management, the SyncAlert Notice Board project offers a comprehensive solution that not only streamlines communication but also enhances organizational productivity and engagement. Its versatility, coupled with user-friendly functionality, makes it an invaluable asset for any setting where clear and timely communication is paramount

RESEARCH ON AESTHETIC COGNITION, FLOW EXPERIENCE AND TECHNOLOGY ACCEPTANCE IN VIRTUAL CULTURAL ACTIVITIES

This research delves into integrating aesthetic experience and technology acceptance within virtual cultural activities, with the primary goal of enhancing user engagement. To achieve this, the study employs a meticulously structured questionnaire to assess participants' aesthetic cognition, flow experience, and acceptance of technology. The methodology involves comprehensive data collection from participants engaged in various virtual cultural events, followed by detailed analytical comparisons to understand user preferences and behaviors. The results clearly indicate a strong preference for immersive and user-friendly technological interfaces. This preference underscores the critical role of aesthetic cognition in determining the success of cultural activities. Furthermore, the findings suggest that significant improvements in interactive features could dramatically enhance user participation and engagement in virtual cultural environments, thereby enriching the overall experience and effectiveness of these activities.