User Engagement Research Articles

Phygital customer journey: a practice-based approach

Purpose The study aims to delve into the “phygital customer journey” (PCJ), which merges physical and digital interactions in customer experiences, using a practice-based lens to reveal the underlying dynamics of these blended encounters. Design/methodology/approach Feedback from 60 individuals established the groundwork for a qualitative analysis. They chronicled customer journeys through diaries and used UXPressia software for journey mapping. This strategy enabled a detailed exploration of the PCJ, focusing on customers’ lived experiences and perceptions. Findings The study presents an integrative framework for the PCJ, identifying four key elements: hybrid artefacts (the melding of digital and physical tools/interfaces), blended contexts (the seamless integration of digital and physical spaces), circular actions (the non-linear paths of customer engagement) and intertwined emotions (the complex emotional responses to phygital experiences). These elements underscore the intricate and interconnected nature of the PCJ. Originality/value This study advances the field by applying a practice-based approach to unravel the complexities of the PCJ, illuminating the nuanced interplay between digital and physical realms. This innovative lens foregrounds the significance of practices in consumer experiences, thereby contributing to a deeper academic and practical understanding of phygital integration.

Augmented reality: the key to unlock customer engagement potential

PurposeThis study aims to investigate the impact of customer perceptions of Augmented Reality (AR) attributes such as augmentation, interactivity and vividness on attitudes towards AR mobile apps, virtual product and behavioural intentions. Also, the mediation role of customer engagement in the effect of perceptions of AR attributes on attitudes and behavioural intentions is examined using the Theory of Interactive Media Effects.Design/methodology/approachThe study used a cross-sectional design. A total of 456 valid data were collected from the Millennials and Generation Z cohorts using purposive sampling. The conceptual framework was assessed using Partial Least Squares-Structural Equation Modelling (PLS-SEM) and Partial Least Squares-Multi Group Analysis (PLS-MGA).FindingsThe research revealed that customer perceptions of AR features such as augmentation, interactivity and vividness significantly influenced customer engagement, leading to favourable attitudes towards both the AR mobile app and the Virtual product as well as behavioural intentions. Furthermore, the study substantiates the role of customer engagement as a mediator in the relationship between customer perceptions of AR attributes and both attitudinal and behavioural outcomes.Originality/valueTo the best of the authors’ knowledge, this is the first attempt to investigate the significance of perceived augmentation as an antecedent to customer engagement and the mediating role of customer engagement on the influence of perceptions of AR attributes on attitudinal and behavioural intention.

A Factorial Randomized Controlled Trial to Optimize User Engagement With a Chatbot-Led Parenting Intervention: Protocol for the ParentText Optimisation Trial.

Violence against children (VAC) is a serious public health concern with long-lasting adverse effects. Evidence-based parenting programs are one effective means to prevent VAC; however, these interventions are not scalable in their typical in-person group format, especially in low- and middle-income countries where the need is greatest. While digital delivery, including via chatbots, offers a scalable and cost-effective means to scale up parenting programs within these settings, it is crucial to understand the key pillars of user engagement to ensure their effective implementation. This study aims to investigate the most effective and cost-effective combination of external components to optimize user engagement with ParentText, an open-source chatbot-led parenting intervention to prevent VAC in Mpumalanga, South Africa. This study will use a mixed methods design incorporating a 2 × 2 factorial cluster-randomized controlled trial and qualitative interviews. Parents of adolescent girls (32 clusters, 120 participants [60 parents and 60 girls aged 10 to 17 years] per cluster; N=3840 total participants) will be recruited from the Ehlanzeni and Nkangala districts of Mpumalanga. Clusters will be randomly assigned to receive 1 of the 4 engagement packages that include ParentText alone or combined with in-person sessions and a facilitated WhatsApp support group. Quantitative data collected will include pretest-posttest parent- and adolescent-reported surveys, facilitator-reported implementation data, and digitally tracked engagement data. Qualitative data will be collected from parents and facilitators through in-person or over-the-phone individual semistructured interviews and used to expand the interpretation and understanding of the quantitative findings. Recruitment and data collection started in August 2023 and were finalized in November 2023. The total number of participants enrolled in the study is 1009, with 744 caregivers having completed onboarding to the chatbot-led intervention. Female participants represent 92.96% (938/1009) of the sample population, whereas male participants represent 7.03% (71/1009). The average participant age is 43 (SD 9) years. The ParentText Optimisation Trial is the first study to rigorously test engagement with a chatbot-led parenting intervention in a low- or middle-income country. The results of this study will inform the final selection of external delivery components to support engagement with ParentText in preparation for further evaluation in a randomized controlled trial in 2024. Open Science Framework (OSF); https://doi.org/10.17605/OSF.IO/WFXNE. DERR1-10.2196/52145.

Saliency-Guided Point Cloud Compression for 3D Live Reconstruction

3D modeling and reconstruction are critical to creating immersive XR experiences, providing realistic virtual environments, objects, and interactions that increase user engagement and enable new forms of content manipulation. Today, 3D data can be easily captured using off-the-shelf, specialized headsets; very often, these tools provide real-time, albeit low-resolution, integration of continuously captured depth maps. This approach is generally suitable for basic AR and MR applications, where users can easily direct their attention to points of interest and benefit from a fully user-centric perspective. However, it proves to be less effective in more complex scenarios such as multi-user telepresence or telerobotics, where real-time transmission of local surroundings to remote users is essential. Two primary questions emerge: (i) what strategies are available for achieving real-time 3D reconstruction in such systems? and (ii) how can the effectiveness of real-time 3D reconstruction methods be assessed? This paper explores various approaches to the challenge of live 3D reconstruction from typical point cloud data. It first introduces some common data flow patterns that characterize virtual reality applications and shows that achieving high-speed data transmission and efficient data compression is critical to maintaining visual continuity and ensuring a satisfactory user experience. The paper thus introduces the concept of saliency-driven compression/reconstruction and compares it with alternative state-of-the-art approaches.

Tides of change: employee training strategies for promoting risk-taking tourism in the North Sea

PurposeThis study critically examines the transformative impact of the “North Sea TikTok” phenomenon on the marine tourism sector, emphasizing the role of employee training in fostering resilience and adaptability within marine economics and integrated marine systems. It delves into how viral social media trends influence marine tourism destinations, particularly the North Sea, affecting local economies, marine resource management and tourism strategies. By analyzing this trend, the paper seeks to uncover how marine tourism destinations can effectively respond to the challenges and opportunities presented by digital media-driven tourism.Design/methodology/approachEmploying a multidisciplinary framework that merges insights from digital marketing, risk perception in tourism and human resource management, this paper provides a comprehensive qualitative analysis of the “North Sea TikTok” trend. Through a meticulous content analysis of viral videos and an examination of user engagement metrics, alongside a thorough review of contemporary literature in marine tourism and sustainability, the study unpacks the far-reaching implications of social media on marine tourism ecosystems.FindingsThe analysis reveals that the “North Sea TikTok” trend has markedly altered public perceptions of the North Sea, catalyzing a shift toward adventure and risk-taking tourism. This pivot promises economic rejuvenation for local tourism sectors and necessitates agile marine management strategies to accommodate the evolving demands. Implementing innovative employee training programs focusing on safety protocols, environmental conservation and digital engagement is central to managing these dynamics. The paper emphasizes integrating sustainable practices to ensure the equitable growth of marine tourism economies and environmental preservation.Originality/valueThis paper pioneers exploring the nexus between social media trends and their operational and strategic impacts on marine tourism management and economics. Synthesizing social media's viral dynamics with marine tourism development introduces groundbreaking insights into adapting marine tourism strategies in the digital age. It emphasizes the critical need for a skilled workforce capable of navigating the complexities of digital trend-driven tourism markets, proposing a novel model for employee training that aligns with the shifting paradigms of marine tourism engagement. This unique contribution advances academic discourse in marine economics and provides practical frameworks for stakeholders aiming to harness social media trends for sustainable tourism development.

Novel data visualization and risk analytic algorithm in a low-middle income country.

To discuss the use of T3™, a data aggregation, visualization, and risk analytic platform in a single centre and its framework for implementation of such a tool in clinical care. We share experience of a tool implemented in a tertiary care Intensive Care Unit (ICU) with limited resources. Superusers were identified and trained. Implementation involved monitoring, evaluation, and user engagement data for continuous emphasis on the use of this tool. Persistent display of T3 data enhanced nursing operational efficiency. Its use was expanded to use in nurses rounds and handover, mortality and morbidity meetings, clinical team teaching through selected teaching cases and analysis of stored data with different research questions. However, lack of infrastructure and technological comprehension, paucity of multidisciplinary teams makes it a challenge in its implementation. Clear framework of implantation and pre-designed studies to determine the clinical usage and effectiveness are important for wide-spread use of such tools.

Beyond the Hype : Building a Personalized Movie Experience with Content-Based Recommendation

This review paper provides a detailed analysis of how a movie recommendation system based on content was planned, executed and evaluated using Streamlit framework. The exponential expansion of digital content has led to the need for efficient recommendation systems, particularly in the realm of movies. In this respect, the proposed recommender system utilizes cosine similarity computations and content-based filtering methods to offer personalized film suggestions relying upon various features such as genres, keywords, castings as well as crews. The author further illustrates rigorous data preparation methods which encompass feature engineering, data collection and cleaning techniques. Furthermore, various other data sources such as TMDb API have been integrated to obtain detailed information about movies. The system, after a thorough study, shows that it has the ability of offering personalized movie recommendations that improve user engagement and experience. This paper examines broader implications of recommendation algorithms and argues their importance for improving happiness and content discovery in digital entertainment platforms. It also raises some common issues encountered during system development and advocates further research work aimed at enhancing recommendation algorithms and making them more flexible and scalable. In this way, it advances our understanding on how personalized content delivery can be applied to shape the landscape of digital entertainment through unmasking the complexities of recommendation systems.

A Review of Machine Learning Approaches for Rumour Detection: Techniques, Challenges, and Future Directions (Machine Learning for Rumour Detection)

Rumours and misinformation propagate rapidly across online social networks, posing significant challenges to maintaining the integrity of information dissemination. In recent years, machine learning (ML) techniques have emerged as promising tools for automating the detection and mitigation of rumours. This review paper provides a comprehensive examination of the advancements in rumour detection using ML approaches. The paper begins by outlining the landscape of rumour dissemination in online social networks, highlighting the characteristics and challenges associated with rumour detection. Subsequently, it systematically categorizes and analyzes various ML methods employed for rumour detection, including supervised, unsupervised, and semi-supervised learning approaches. Furthermore, the review delves into the diverse features and representations utilized in ML models for rumour detection, such as textual content, user engagement patterns, network structures, and temporal dynamics. It discusses the strengths and limitations of different feature sets and their impact on the effectiveness of rumour detection systems. Moreover, the paper explores the intricacies of dataset construction and evaluation methodologies for training and testing rumour detection models. It examines commonly used benchmark datasets and evaluation metrics, emphasizing the importance of robust evaluation frameworks for assessing the performance of ML-based rumour detection systems accurately. Additionally, the review identifies key challenges and open research questions in the field of rumour detection using ML, including handling evolving rumour patterns, addressing adversarial attacks, and enhancing the interpretability and explain ability of ML models. It also discusses potential directions for future research aimed at advancing the state-of-the-art in rumour detection and mitigation.

“Customer engagement and advertising : Looking forward and backward”

This report presents the interaction between consumer strategy and advertising, examines the history and future projections of advertising practices. . Technological advances, cultural shifts, and changes in consumer preferences have led to changes in consumer engagement and advertising. By analyzing backwards from the previous period, from daily media to digital platforms, important information about good ideas, problems encountered and lessons are written down. The future direction of advertising includes technologies such as artificial intelligence, virtual reality and experience. Expected changes in consumer behavior,regulatory environment and new business opportunities are explored to provide businesses and marketers with a positive outlook. Advise clients on collaboration and advertising strategies in a complex and competitive market. Methodology/Design: The researcher conducted interviews using a qualitative method to gather information about the Customer engagement and advertising: looking forward and backward. Through these interviews, the study aims to identify current challenges and opportunities, using evidence to inform future recommendations. Research: Research shows that the advertisements are structured in a way that it engages the customer with considering and analysing traditional trends and future success. Research participant highlighted the issues, trends, solutions of customer’s engagement and advertising also with navigating the old traditional strategies and future ones. This report also shows the values that are added through advertisements and ultimately results in increased sales for the business Value/Value: The report provides values such as information, innovation, change, ethics, sustainability,longterm relationships, competitive advantage and customer satisfaction for businesses to improve their customer engagement and advertising strategies. focused approach to advertising and customer engagement. By understanding and meeting the needs and preferences of your target audience, businesses cancreate effective and relevant marketing plans.

MARKETING STRATEGIES AMUL ICE-CREAM IN NOIDA

This essay explores new ways of advertising Amul Ice Cream in the ever-changing Noida market. Noida is a metropolis with a diverse population and a fast growing client base, providing Amul with ample opportunities for growth. After researching the local market, customer tastes, and competitors extensively, this report offers strategic positioning and promotion ideas for Amul Ice Cream. Some examples of these strategies include developing regionally specialized flavors, utilizing innovative packaging designs, forming partnerships with local businesses and events to increase product visibility, and utilizing digital platforms for more targeted promotion and interaction. Promoting a company's commitment to offering reasonably priced, high-quality products is a certain way to boost brand trust and loyalty. Amul can strengthen its position and drive growth in the fiercely competitive ice cream sector with these innovative marketing strategies tailored to the Noida market. Keywords: Amul Ice Cream, Noida, marketing strategies, product differentiation, distribution channels, promotional activities, customer engagement.

ONLINE ADVERTISING AND IT’S IMPACT ON CONSUMER BUYING BEHAVIOUR

Keeping in mind the ever-changing landscape of digital marketing, this study investigates the impact of online advertisements on customers' buying behaviors. The proliferation of online platforms and the increasing number of internet users present an opportunity for businesses to advertise to individuals. The fundamental objective of this research is to figure out how online advertising affects customers' emotions, decisions, and actions. This study synthesises existing literature, empirical data, and theoretical frameworks to investigate the many ways via which online advertising influences consumer behavior. The significance of targeted advertising in identifying and appealing to certain consumer demographics, the persuasive tactics employed by online ads, and the influence of social media endorsements and user-generated material on intents to purchase are all major aspects that are being investigated. The study's key findings indicate that online advertising significantly influences customers throughout the entire buying process, from first awareness and consideration through purchase and post-purchase actions. Customer engagement and brand memory can be enhanced through personalized and immersive advertising experiences made possible by the interactive nature of web platforms. Online content can be made more credible and trustworthy by adding social proof and peer endorsements. This, in turn, influences consumers' purchasing decisions. The ramifications of these results should be carefully considered by marketers and advertisers who wish to make the most of their advertising budgets and make the most of their online advertising strategies. By studying what makes people react to internet ads, businesses may refine their messaging, creative content, and targeting strategies. Because of this, they will be able to connect with their intended consumers and achieve their goals. Keywords: online advertising, consumer buying behavior, digital marketing, persuasive techniques, targeted advertising, social media endorsements, consumer engagement, purchase intentions.

The politics of allyship: Multiethnic coalitions and mass attitudes toward protest

Recent work finds that nonviolent resistance by ethnic minorities is perceived as more violent and requiring more policing than identical resistance by ethnic majorities, reducing its impact and effectiveness. We ask whether allies-advantaged group participants in disadvantaged group movements-can mitigate these barriers. On the one hand, allies can counter negative stereotypes and defuse threat perceptions among advantaged group members, while raising expectations of success and lowering expected risks among disadvantaged group members. On the other hand, allies can entail significant costs, carrying risks of cooptation, replication of power hierarchies, and marginalization of core constituencies. To shed light on this question we draw on the case of the Black Lives Matter (BLM) movement, which, in 2020, attracted unprecedented White participation. Employing a national survey experiment, we find that sizeable White presence at racial justice protests increases protest approval, reduces perceptions of violence, and raises the likelihood of participation among White audiences, while not causing significant backlash among Black audiences. Black respondents mostly see White presence as useful for advancing the movement's goals, and predominant White presence reduces expectations that protests will be forcefully repressed. We complement these results with analysis of tens of thousands of images shared on social media during the 2020 BLM protests, finding a significant association between the presence of Whites in the images and user engagement and amplification. The findings suggest that allyship can be a powerful tool for promoting sociopolitical change amid deep structural inequality.

Evaluation of TikTok videos on acute pancreatitis: content quality and reliability analysis

BackgroundAcute pancreatitis (AP) is a common acute digestive system disorder, with patients often turning to TikTok for AP-related information. However, the platform’s video quality on AP has not been thoroughly investigated.ObjectiveThe main purpose of this study is to evaluate the quality of videos about AP on TikTok, and the secondary purpose is to study the related factors of video quality.MethodsThis study involved retrieving AP-related videos from TikTok, determining, and analyzing them based on predefined inclusion and exclusion criteria. Relevant data were extracted and compiled for evaluation. Video quality was scored using the DISCERN instrument and the Health on the Net (HONcode) score, complemented by introducing the Acute Pancreatitis Content Score (APCS). Pearson correlation analysis was used to assess the correlation between video quality scores and user engagement metrics such as likes, comments, favorites, retweets, and video duration.ResultsA total of 111 TikTok videos were included for analysis, and video publishers were composed of physicians (89.18%), news media organizations (13.51%), individual users (5.41%), and medical institutions (0.9%). The majority of videos focused on AP-related educational content (64.87%), followed by physicians’ diagnostic and treatment records (15.32%), and personal experiences (19.81%). The mean scores for DISCERN, HONcode, and APCS were 33.05 ± 7.87, 3.09 ± 0.93, and 1.86 ± 1.30, respectively. The highest video scores were those posted by physicians (35.17 ± 7.02 for DISCERN, 3.31 ± 0.56 for HONcode, and 1.94 ± 1.34 for APCS, respectively). According to the APCS, the main contents focused on etiology (n = 55, 49.5%) and clinical presentations (n = 36, 32.4%), followed by treatment (n = 24, 21.6%), severity (n = 20, 18.0%), prevention (n = 19, 17.1%), pathophysiology (n = 17, 15.3%), definitions (n = 13, 11.7%), examinations (n = 10, 9%), and other related content. There was no correlation between the scores of the three evaluation tools and the number of followers, likes, comments, favorites, and retweets of the video. However, DISCERN (r = 0.309) and APCS (r = 0.407) showed a significant positive correlation with video duration, while HONcode showed no correlation with the duration of the video.ConclusionsThe general quality of TikTok videos related to AP is poor; however, the content posted by medical professionals shows relatively higher quality, predominantly focusing on clinical presentations and etiologies. There is a discernible correlation between video duration and quality ratings, indicating that a combined approach incorporating the guideline can comprehensively evaluate AP-related content on TikTok.

Scientific dissemination and social networks: a look at the use of Instagram in scientific divulgation

Social networks allied to technology made access to information faster but did not predict the legitimacy of this information. Scientific divulgation in social networks emerges to present the scientific method in didactic way with simple language, without jargon, especially in a pandemic era, of search for results and scientific understanding. According with this, the page “algas para que te quero” was created on Instagram, about the work area in Marine Biotechnology, and the use of algae in this environment, to understand the impact, difficulties and reach of the theme to the public in general. Therefore, the present work brought positive results. After a year on the page, in the insights (a resource of the platform itself), a total of 3.140 views were reached, conquering 399 followers, with an average interaction of 57.9%. The data demonstrated that there was a significant participation and interaction of users with the content provided.

Assessing the perceived value of a user-led educational intervention to support recovery in a Swedish psychiatric organization: A qualitative case study.

Many people with mental health issues recover and re-establish their identity and find hope and meaning in life, irrespective of symptom burden. Recovery can be supported through learning and education, aiming at strengthening self-management and coping skills. Such education offered by peers with lived experience is rare and scarcely reported. The aim was to assess the perceived value of an educational intervention, called the Patient School (PS), organized within a psychiatry organization by employed patient peers with lived experience. A qualitative case study based on interviews with people with mental health issues (n = 8), peer-organizers (n = 4) and healthcare professionals (n = 4), and documents such as schedules and educational materials were used. First, the interviews were transcribed and analyzed using inductive conventional content analysis. Second, the findings were synthesized into a programme theory, illustrated in a logic model. The perceived value of the PS was related to the willingness of peer-organizers to share their own experiences, a sense of belonging, sharing with like-minded and new knowledge, practical skills, roles and attitudes acquired. These experiences were empowering, decreased stigma and reassured user participants that one's identity is not defined by mental health issues. This increased self-confidence paves the way for increased self-management and creates a potential for a more efficient use of healthcare services. We conclude that this PS, organized within a psychiatry organization by salaried peers, achieved the same positive results as those reported in the literature and showed the value of having peer-organizers being part of the staff. This research was performed in a partnership between academic researchers and persons with user experience of psychiatric services, engaged in the educational intervention in the focus of the study. The research plan was co-designed, and the analysis of the data collected was performed in collaboration. The participation of the co-researchers with user experience gave the project team access to the study site, provided the team with insights into to study context and contributed with an understanding promoting the interpretation of the findings.

EVALUATING THE EFFECTIVENESS OF SOCIAL MEDIA MARKETING STRATEGIES IN DRIVING SALES: A CASE STUDY OF SNAPDEAL IN THE INDIAN ONLINE MARKETPLACE

This paper investigates the efficacy of social media marketing strategies in bolstering sales performance, with a specific focus on Snapdeal, a prominent player in the Indian online marketplace. In an era where digital connectivity is paramount, social media platforms have become indispensable tools for businesses seeking to enhance their market presence and drive revenue growth. Through a comprehensive analysis of Snapdeal's social media marketing approach, including targeted advertising, customer engagement, influencer partnerships, and content marketing, this study aims to elucidate the impact of these strategies on driving sales in the Indian e-commerce landscape. By examining Snapdeal's utilization of social media platforms to engage with its diverse consumer base, foster brand loyalty, and influence purchase decisions, this research provides valuable insights into the evolving role of social media in shaping consumer behavior and driving business success in the digital age. Keywords:- Social Media, Marketing Strategies, Snapdeal , India , Online Evaluation

A Mixed Methods Pilot Study to Evaluate User Engagement with MedMicroMaps: A Novel Interactive E-learning Tool for Medical Microbiology

A Mixed Methods Pilot Study to Evaluate User Engagement with MedMicroMaps: A Novel Interactive E-learning Tool for Medical Microbiology

Blockchain based Decentralized Application

This research article provides an overview of business applications (DApps) in the context of blockchain innovation. It includes the definition, structure and classification of DApps, highlighting their focus and challenges. It also examines the importance of distribution, security, user participation, flexibility, collaboration, and governance in DApp development. The article also examines smart contracts, protocols, APIs, and independent independent organizations (DAOs) when implementing DApps. Overall, it highlights the importance of blockchain innovation in this field, offering some information and advice to designers and partners interested in creating DApps.

Dual-blend insight recommendation system for e-commerce recommendations and enhance personalization

E-commerce, short for electronic commerce, refers to the buying and selling of goods and services over the internet. This digital transaction model has revolutionized the way businesses operate and consumers shop. In response to the burgeoning complexity of e-commerce datasets, this work addresses the need for advanced recommendation systems. This work introduces the dual-blend insight recommendation system (DIRS) model for personalized e-commerce recommendation system. The DIRS model involves dataset loading, preprocessing, and feature extraction, enabling training with recurrent neural network (RNN) and Bayesian personalized ranking (BPR) models. Recommendations are generated based on user-defined functions, i.e., location and session, and evaluation metrics such as hit rate (HR) and mean reciprocal rate (MRR) highlight DIRS’s superior performance. The model is evaluated using the Tmall dataset. Results reveal DIRS consistently outperforms alternative algorithms, showcasing its effectiveness in 10k and 20k recommendation sets. This study provides valuable insights into optimizing e-commerce recommendations, emphasizing DIRS as a powerful model for enhancing user experience and engagement.

Impact of Artificial Intelligence in Companies Marketing Strategies

Impact of Artificial Intelligence in Companies Marketing Strategies