User Engagement Research Articles

Unpacking the complexity of online incivility: an analysis of characteristics and impact of uncivil behavior during the Hong Kong protests

PurposeThis study seeks to establish a new framework for categorizing incivility, differentiating between explicit and implicit forms, and to investigate their respective abilities to proliferate and mobilize conversations, along with behavioral outcomes in various social contexts.Design/methodology/approachEmploying computational techniques, this research analyzed 10,145 protest-related threads from the HK Golden Forum, a prominent online discussion board in Hong Kong.FindingsOur analysis revealed divergent effects of explicit and implicit incivility on their diffusion, influences on deliberative discussions, and user participation. Explicit incivility was found to impede deliberative conversations, while implicit incivility tended to provoke more responses. Explicit uncivil expressions encouraged the propagation of incivility but reduced the likelihood of individual involvement. In contrast, implicit incivility had a stronger dampening effect on further uncivil comments and achieved greater thread popularity. The results showed strong associations between uncivil expressions and the contextual norms surrounding social movements.Originality/valueTheoretically, this research introduced a classification of incivility and underscored the importance of differentiating between implicit and explicit incivility by examining their effects on deliberation and engagement. Although previous studies have extensively covered explicit incivility, this study goes further by analyzing implicit incivility and comparing both forms of uncivil discourse in a less-studied context. Methodologically, the study developed a Cantonese dictionary to differentiate between two types of incivility, providing a practical reference for more nuanced analyses. By revealing how varying movement norms moderate the interplay between deliberative and uncivil expressions, the study drew attention to the highly situational nature of incivility.

Preliminary study on the feasibility of approximating children's engagement level from their emotions estimation by a picture-based, three-model AI in a family-robot cohabitation scenario

Haru4Kids (H4K) is a system that emulates the physical, social, family-oriented robot Haru, designed with the goal of cohabitating with children in their homes for extended periods of time. In a previous experiment [Garcia GA, Perez G, Levinson L, et al. Living with Haru4Kids: study on children's activity and engagement in a family-robot cohabitation scenario. In: 2023 IEEE ROMAN; 2023 Aug. p. 1428–1435], seven families kept H4K for a span of two weeks in their homes. Throughout this period of cohabitation, we collected child-robot interaction data, including images that were later hand-annotated to estimate user engagement. In this present work, we used a novel AI-based, four-stage framework available from Roboflow for the automatic estimation of children's level of engagement from their inferred emotions. We did a deep study of the performance and behaviour of that framework over our dataset of users' pictures and characterized its response in order to understand its advantages and limitations, including the technique used to translate emotions into engagement levels. We also tested a different approach for that mapping, using a machine learning technique based on Support Vector Machine (SVM). The framework yielded promising results just ‘off-the-shelf’: 0.47–0.68 accuracy and 0.46–0.70 F1 using the original mapping, and 0.39–0.75 and 0.37–0.78 respectively using SVM. Therefore, we propose this emotion-based approach for engagement estimation from pictures.

Data visualisation for decision making under deep uncertainty: current challenges and opportunities

Abstract This perspective article explores the role of data visualisation in decision-making under deep uncertainty (DMDU), a growing discipline tackling complex socio-environmental challenges, such as climate impacts and adaptation, natural resource management, and preparedness for extreme events. We discuss the role of visualisation for both analysis (or exploratory) purposes, as well as communication (or explanatory) purposes, including to stakeholders and the public. We identify a lack of comprehensive guidelines on how visualisations are currently used and their potential in enhancing DMDU processes. Drawing on literature and insights from a recent workshop, we identify key challenges DMDU analysts face when visualising data: managing complexity and dimensionality, effectively communicating uncertainty, and ensuring user engagement and interpretability. We propose a research agenda to address these challenges, by taxonomising and evaluating the effectiveness of different visual forms in decision-making contexts, and fostering interdisciplinary collaboration. We argue that, through these efforts, we can improve the communication and usability of DMDU analyses, ultimately aiding in more informed and adaptive decision-making in the face of deep uncertainty.

A Roadmap for the Design of a Public-participation Geographic-Information System to Support Urban Ageing

Geospatial technologies have the potential to transform the lives of older adults by providing them with necessary tools to navigate their local communities, access services, connect with others, and access valuable information. However, the usability and accessibility of such technologies often fall short of the needs of older adults. Many existing geospatial tools are not designed with the needs and preferences of older adults in mind; this can lead to usability challenges and limit their usage. This paper explores a participatory approach in developing an inclusive geodata-collection tool that is specifically tailored to older users’ needs. The paper also highlights the importance of incorporating user-centered design principles, participatory design methods, and accessibility guidelines throughout the entire geodata-tool-development process. It also emphasizes the need for ongoing user engagement and feedback in order to ensure that the tool remains relevant and usable in the evolving digital landscape. This participatory approach has resulted in a tool that is easy to use and accessible for older adults; it is available in various languages, thus ensuring that the elderly can actively participate in the prototype’s creation and contribute to the collection of the geospatial information that reflects their lived experiences and needs.

Decoding Clickbait: The Impact of Clickbait Types and Structures on Cognitive and Emotional Responses in Online Interactions.

This study delves into the influence of clickbait types (hyperbole, insinuation, visual rhetoric, and puzzle) and structures (emotion-label and emotion-laden words) on user cognitive and emotional responses in an online environment. Using electroencephalography with 32 internet-experienced participants, we analyzed how these different clickbait configurations affect engagement and processing. Our findings highlight that clickbait types such as hyperbole and visual rhetoric swiftly capture attention and enhance emotional engagement, whereas insinuative and puzzling clickbait demand more cognitive effort and deeper processing. In addition, the structure of emotional words significantly influences user responses; emotion-laden words facilitate quicker cognitive processing and enhance emotional reactions, particularly in contexts involving negative emotions. These insights offer valuable implications for content creators and marketers in strategizing ethical clickbait usage, aiming to balance user engagement with information integrity. This research contributes to a nuanced understanding of the interplay between content presentation and user perception, providing a foundation for future explorations into ethical digital content practices.

Predicting Consumer Behavior in E-Commerce Using Recommendation Systems

As e-commerce platforms continue to expand, understanding consumer behavior has become crucial for enhancing customer satisfaction and driving business success. Recommendation systems play a pivotal role in predicting consumer preferences and delivering personalized product suggestions. This paper presents an extensive literature review on recommendation techniques, including collaborative filtering, content-based approaches, and hybrid models. Notable advancements, such as the use of deep learning, trust-based filtering, and context-aware models, are highlighted. Building on these foundations, we propose a novel model that integrates advanced machine learning algorithms with consumer behavior analysis to predict preferences more accurately. The expected results suggest that this model will improve the precision of recommendations, effectively addressing challenges like data sparsity and evolving user preferences and enhancing overall customer engagement in e- commerce environments.

Revolutionizing Customer Service : The Impact of Large Language Models on Chatbot Performance

This article examines the transformative impact of Large Language Models (LLMs) on customer service chatbots across various industries. Through a comprehensive analysis of case studies, the article explores the implementation strategies, performance metrics, and technological advantages of LLM-powered chatbots in sectors including e-commerce, telecommunications, financial services, healthcare, and travel. The article highlights the advanced capabilities of LLMs in natural language understanding, response generation, and continuous learning, demonstrating their potential to significantly enhance customer interactions and operational efficiency. The article also addresses key technical challenges in implementing LLM chatbots, such as data privacy, response accuracy, and scalability, offering potential solutions for each. Finally, it discusses future directions for LLM-powered chatbots, including multimodal capabilities, emotion recognition, and predictive customer service, providing insights into the evolving landscape of AI-driven customer engagement.

Social Media User’s Engagement’s Function And Measurements On Marketing Communication 4.0

In the era of Industry 4.0, social media user engagement contributed to the effectiveness of marketing communications. Companies that use social media as communication marketing channels are still trying to define the concept of engagement according to the subjective understanding and definition of measurement offered by social media insights. This article provides an update on the concept of social media user engagement in the context of marketing communication in Indonesia. Through a qualitative approach to the study of literature and interviews with some informants who use social media as a marketing communication platform, it was found that the involvement of social media users serves to measure and find patterns of content that are effectively used for marketing communication. In general, social media user engagement can also be grouped into three dimensions: affective, cognitive, and behavioral engagement.

Developing a Workflow for Transforming BIM Models into Immersive Virtual Reality Experiences

Abstract. The integration of Extended Reality (XR) and Building Information Modelling (BIM) has emerged as a promising approach for enhancing interaction with spatial data in the built environment. While the potential of BIM for advanced visualization has been recognized, there remains a need for standardized workflows that facilitate the transformation of BIM models into immersive virtual reality (VR) experiences. This research contributes to the ongoing development of BIM-VR integration by presenting a workflow that leverages Revit, Twinmotion, and Datasmith to create visually rich and interactive VR environments. The established process focuses on enhancing textures, incorporating dynamic lighting and weather simulations, and populating the virtual space with realistic elements. The workflow also addresses the integration of interactable objects to elevate user engagement and the use of cutting-edge VR headsets for an immersive experience. By providing a structured approach to bridging complex BIM data with VR, this research aims to support architects, engineers, construction professionals, and clients in design collaboration, project review, and decision-making across the building lifecycle. The workflow's potential for facilities management and training applications is also explored. Through a case study, the research demonstrates the workflow's effectiveness in facilitating a deeper understanding of architectural spaces before construction, highlighting its potential for improving efficiency and reducing rework. The paper also discusses the challenges and opportunities associated with integrating BIM with GIS and sensor data to create comprehensive digital twins. This research contributes to the growing body of knowledge on BIM-VR integration and underscores the importance of continued development in this field to enhance the design, communication, and experience of the built environment.

Geopolitics, Privacy, and User Trust: TikTok

The paper uses a thorough review of the current literature, governmental materials, and information available on ByteDance as the major source for analyzing the link between geopolitical aspects, privacy concerns, and user engagement with businesses. The study found that the uncertainty surrounding TikTok’s data usage and the ongoing tensions between China and the United States leads to a decline in user trust. This is particularly evident in the e-commerce sector, where individual privacy concerns directly affect customers’ buying habits and commercial involvement. This phenomenon would directly impact TikTok’s international e-commerce expansion, as well as user engagement on the platform; ultimately affect the platform’s overall growth and revenue potential. The paper concludes with recommendations for enhancing data privacy on TikTok such as reducing data collection from minors, putting stricter regulations on third-party data access and being more transparent about their data policies.

LAW, SOCIAL MEDIA, AND THE KARAOKE BUSINESS

Intellectual property law, particularly copyright law, is a significant challenge for karaoke businesses. The necessity of obtaining proper music licenses is well-understood, but the complexities and costs involved often lead to gaps in compliance. Local regulations, including zoning laws, noise ordinances, and alcohol licensing, further complicate the legal landscape for karaoke operators. Non-compliance with these laws can result in severe penalties, including fines, legal disputes, and potential business closures. Social media has emerged as an essential tool for marketing and customer engagement in the karaoke industry. Platforms like Facebook, Instagram, and TikTok enable businesses to reach a broader audience and create interactive experiences that enhance customer loyalty. However, the use of copyrighted music in social media posts poses significant legal risks. While social media offers opportunities for growth, businesses must navigate these platforms carefully to avoid copyright infringement and other legal challenges. Managing online reputations is critical in the age of social media, where negative reviews or viral posts can significantly impact a business's image. Proactive strategies for handling customer feedback and maintaining a positive online presence are essential for mitigating reputational risks. The regulatory environment for karaoke businesses is evolving, with stricter enforcement of copyright laws and changing social media policies. Businesses must stay informed and adapt to these changes to ensure continued compliance and operational success. Karaoke businesses should prioritize legal education and seek expert guidance to navigate the complexities of copyright law and other regulatory requirements effectively. Clear social media policies that address the use of copyrighted material and customer interactions are vital for minimizing legal risks and maximizing the benefits of digital marketing. Implementing robust reputation management strategies, including prompt responses to online reviews and engagement with customers, can help maintain a positive public image and reduce the impact of negative feedback. Businesses should monitor changes in copyright enforcement and social media regulations, adapting their practices accordingly. Forming partnerships with music rights organizations or utilizing technology solutions can streamline compliance efforts.

An In-depth Analysis of Consumer Perceived Value and Expansion of Online Retailers in Metropolitan Kampala, Uganda

Purpose: This study aims to conduct an in-depth analysis of how consumer perceptions of value shape purchasing decisions and foster sustained expansion for online retailers in Metropolitan Kampala, Uganda. The study will identify the key theoretical foundations that anchor research on perceived value, provide actionable insights to guide online retailers in developing effective strategies for overall business growth and propose a future research agenda on Perceived Value. Methodology: This review process was organized on the three-stage method: planning, execution, and reporting. In the first stage, the study identified its purpose and selected its main source of data being peer-reviewed journals from EBSCOHost, Econlit, Google Scholar, Web of Knowledge, and Social Sciences Citation Index. During the execution stage, Consumer Perceived Value, Online Retailers, and e-commerce are the identified keywords to facilitate the search for data. Out of 63 publications obtained between 2015 and 2024, only 26 papers were examined after reading the abstracts. The findings were reported using tabulation and narration. Findings: The findings highlight how enhancing perceived value through effective e-marketing strategies, quality service, and personalized experiences can lead to increased customer engagement, retention, and ultimately, the successful adoption of e-commerce technologies. Dive in to discover how businesses can differentiate themselves in a competitive market by focusing on what truly matters to their customers. Technology Acceptance Model (TAM), service quality Theory (S.Q.T), and Unified Theory of Acceptance and Use of Technology (UTAUT) have been identified as the dominant theoretical framework in the study on consumer perceived value (P.V.). Implications: Businesses that effectively enhance perceived value through improved service quality, customer engagement, focus on creating a balanced approach to convenience, privacy, and build and maintain good relationships with customers can differentiate themselves in competitive markets. Exploring the constraints of the reviewed studies offers potential research directions. This study, therefore offers a complete perspective that advances both practice and research.

Analysis of Successfully Brand positioning & extending on customer engagement: A Study case of UNIQLO Retail Store

Analysis of Successfully Brand positioning & extending on customer engagement: A Study case of UNIQLO Retail Store

Learning from Experts by Experience as Part of Social Work Education: Undergraduate Students’ Perspectives

ABSTRACT In the last decade, various experiences have been organized aimed at helping future social work education professionals reflect on the power relationships that define institutions and social policies. These experiences, based on the participation of users of social services (now known as experts by experience (EBE) and as part of service user involvement (SUI), aim to create opportunities for shared learning based on mutual knowledge and understanding of the worlds of others. The research described in this article focuses on the impact that SUI experiences had on future social educators who participated in three (so far) 14-week courses in which fifteen students and a group of EBEs learnt together. Undergraduate students were asked to evaluate the course methodology, the skills they acquired and what they learnt, via two focus groups and 45 individual narrative reports. The results showed that students appreciated learning together in a safe environment, collaborating on activities. They felt that participation helped them improve their socio-personal skills and advance their professional development. They valued the importance of learning together as an instrument of social transformation. Our research suggests that SUI or EBE involvement experiences, based on learning together in initial training as an instrument for transforming socio-educational professional practices, are valuable.

Financial Performance Evaluation of Fast-Food Restaurant

This study examines McDonald's financial performance from 2019 to 2023, focusing on key financial metrics such as profitability, operational efficiency, liquidity, solvency, and cash flow. The objective is to assess McDonald's financial health and identify factors contributing to its sustained market leadership in the fast-food industry. Using descriptive statistics and regression analysis, the study evaluates McDonald's financial ratios, including operating profit margin, return on assets, inventory turnover, and current ratio, among others. The results reveal strong profitability and effective cost control, with a consistent operating profit margin and robust asset management. McDonald's liquidity is sufficient to meet short-term obligations, and its prudent debt management reflects financial stability. The company’s investment in digital transformation and operational improvements, such as streamlined inventory management and enhanced customer engagement, have further contributed to its financial resilience. In conclusion, McDonald's has demonstrated adaptability and resilience amidst external challenges, ensuring continued financial success. The study suggests that McDonald's should continue investing in digital platforms and menu innovation to meet evolving customer preferences. The implications of these findings are significant for the fast-food industry, highlighting the importance of strategic financial management in maintaining market leadership and long-term growth

Participatory Community Learning to Develop a Digital Market Management System for Community Enterprises and Stable Occupation Groups Nam Phrik Kaeng Krua Khanong, Song Khanong Subdistrict, Sam Phran District, Nakhon Pathom Province

Background and Aim: Digital Marketing Management is critical for successfully promoting products and services in the digital age. It allows businesses to reach a larger audience, interact with customers in real-time, and tailor strategies based on data insights to boost growth and brand awareness. This study investigates the digital marketing practices of the Song Khanong Occupation Group in Prik Kaeng Krua Khanong, Nakhon Pathom Province, aiming to enhance customer engagement, brand awareness, and sales outcomes by focusing on Generation Z and Baby Boomers. Materials and Methods: A mixed-methods approach was utilized, combining surveys of 200 community members on digital media usage, content preferences, brand perception, and customer satisfaction, along with interviews with key stakeholders about marketing strategies. Data analysis involved calculating mean scores to assess satisfaction with digital marketing elements. Results: Results showed high satisfaction among Generation Z, with Facebook as the preferred platform (mean score: 4.86). Infographics and videos received the highest scores (4.93 and 4.80, respectively), while Baby Boomers valued brand aesthetics (overall score: 4.77). Tools like Chatbots and QR Codes enhanced user experience significantly. Conclusion: The study underscores the need for effective digital marketing strategies in community enterprises to boost engagement and brand recognition. High satisfaction levels indicate that tailored content and a robust online presence are essential for customer retention. Future efforts should focus on continuous improvement and leveraging technology for better communication, enabling sustainable growth for community enterprises in Song Khanong.

Enhancing Customer Engagement in Insurance Companies Using Salesforce Journey Builder: Tracking Customer Journeys Through Email Open and Ad Clicks

In the competitive insurance industry, understanding and engaging customers throughout their journey is crucial for retaining existing clients and acquiring new ones. Salesforce Marketing Cloud's Journey Builder provides a powerful platform for designing and automating personalized customer experiences. This paper explores how insurance companies can leverage Journey Builder to track and analyze customer interactions such as email opens, and ad clicks. Detailed explanations of journey flows, including the use of Apex code for integrations, are provided. Key Performance Indicators (KPIs) essential for measuring the success of these customer journeys are highlighted. An illustrative example is included to demonstrate the practical application of Journey Builder in enhancing customer engagement within the insurance sector. Keywords: Salesforce Journey Builder, Insurance Industry, Customer Engagement, Marketing Cloud, Apex Code, Customer Journey Tracking, Email Opens, Ad Clicks, KPIs

How do customers react to the integration of AI in customer experience

Artificial Intelligence is revolutionizing customer service through enhanced customization and efficiency. Processing natural language makes interactions more human-like and guarantees higher levels of customer satisfaction. With the help of AI-enabled Chatbots communication with users occurs instantaneously, answering their questions and providing immediate responses. By forecasting preferences and suggesting recommendations through the evaluation of data collected on customers, artificial intelligence improves service quality. The amalgamation of modern technology and customer service provides a smooth, personalised and linear client experience. While AI-driven chatbots and tools prove time and cost-effective, occasional delays or failures instil human hesitation. The escalating trend of integrating AI in customer service significantly enhances the overall human experience, according to various studies. However, this study aims to address a dearth of empirical research on AI-enabled customer experiences. The absence of emotional intelligence in current AI models contributes to lacklustre customer commitment and engagement. This study investigates how customers react to Artificial intelligence being integrated into the customer service industry. The study scrutinizes pivotal factors—Perceived trustworthiness, personalization, perceived ease of use, perceived usefulness, accuracy, and quality of information provided—examining their interdependence in augmenting the customer experience. This study will utilise a proposed model which utilises the stimulus, organism, and response model. Results underscore how these factors contribute to improving customer loyalty through the mediation role of customer engagement. Hence, the study reveals the interconnectedness of these factors with brand affinity and loyalty, emphasizing the importance of these factors in fostering lasting customer relationships.

The Impact and Future of Generative Pre-trained Transformers: A Study of GPT in Enhancing Business and Technology

With the development of artificial intelligence (AI), natural language processing (NIP) has clearly become the key to enhancing AI capabilities, especially through the deployment of GPT. This paper explores the major advances and related commercial applications of GPT, as it is at the cutting edge of AI technology with far-reaching capabilities in terms of text generation, language understanding, and human-machine interaction. Developed by OpenAI, GPT uses innovative transformer architecture to make breakthroughs in a variety of language tasks, marking a major evolution in the potential applications of AI in various industries. This research explores the integration of GPT in sectors, highlighting how its complex text processing capabilities can be utilized to improve efficiency and innovative service delivery. The study highlights the transformative impact of GPT on business efficiency, strategic decision-making, and customer engagement, thanks to its scalable and adaptable AI framework. Finally, the document reflects the need for a strong ethical framework and regulatory supervision to guide the deployment of GPT technologies. As the Global Trade Agreement evolves, it is committed to shaping the future of global industry by promoting innovation while calling for a balanced approach to ethical considerations and social impacts.

Integrating ChatGPT with Salesforce for Real-Time Market Insights on Accounts

This paper explores the integration of ChatGPT, an AI-driven natural language processing model, with Salesforce to enhance sales teams' access to real-time market information about specific accounts. By integrating ChatGPT with Salesforce through API calls, users can fetch the latest market trends, news articles, stock prices, financial data, legal filings, and acquisitions related to specific accounts directly on the Account detail page. This integration not only improves decision-making and customer engagement but also offers a scalable, automated solution that saves time and enhances data accuracy. The paper includes coding examples, architecture diagrams, and use cases to demonstrate the implementation, and it discusses key performance indicators (KPIs) for assessing its effectiveness in real-world applications. Keywords: Salesforce, ChatGPT, AI Integration, Real-Time Data, Account Insights, API, Market Trends, CRM, Natural Language Processing, Automation