Search Results (47)

Water utilities are increasingly turning to digital solutions to promote conservation behaviours among households; however, traditional campaigns often suffer from limited personalisation, low interactivity, and modest long-term impact. Though computer-tailored and recommender systems (RSs) may offer personalisation, these systems lack a generalised framework that integrates behavioural theory with system design. This study addresses this research gap by introducing a novel framework that unites behavioural science, user experience (UX) design, and adaptive digital feedback to foster water-conscious practices at the residential level. The model draws on established behavioural theories, including the Theory of Planned Behaviour, the Transtheoretical Model, and Intervention Mapping, to ensure that tailored recommendations align with users’ psychological drivers, behavioural readiness, and daily routines. An industry-first prototype RS was developed and evaluated through an online survey (N = 300), assessing user perceptions of relevance, motivation, ease of use, and likelihood of action. The results reveal strong support for personalised suggestions, with 82% of respondents agreeing that personalised recommendations would help conserve water, and 76% indicating incentives would motivate adoption. This evidence indicates early acceptance and high potential impact. This study also addresses a critical research gap: no generic model previously existed to guide the integration of RSs with behaviour change interventions in water demand management. Broader implications are also discussed for applying the model to other sustainability domains such as energy use, waste reduction, and climate adaptation. Full article

Background/Objective: The global acceleration of population aging presents profound challenges to the physical, psychological, and social well-being of older adults. As traditional exercise programs face limitations in accessibility, personalization, and sustained social support, there is a critical need for innovative, inclusive, and community-integrated digital movement solutions. This study aimed to develop and evaluate Movement Poomasi, a hybrid digital healthcare application designed to promote physical activity, improve digital accessibility, and strengthen social connectedness among older adults. Methods: From March 2023 to November 2023, Movement Poomasi was developed through an iterative user-centered design process involving domain experts in physical therapy and sports psychology. In this study, the term UI/UX—short for user interface and user experience—refers to the overall design and interaction framework of the application, encompassing visual layout, navigation flow, accessibility features, and user engagement optimization tailored to older adults’ sensory, cognitive, and motor characteristics. The application integrates adaptive exercise modules, senior-optimized UI/UX, voice-assisted navigation, and peer-interaction features to enable both home-based and in-person movement engagement. A two-phase usability validation was conducted. A 4-week pilot test with 15 older adults assessed the prototype, followed by a formal 6-week study with 50 participants (≥65 years), stratified by digital literacy and activity background. Quantitative metrics—movement completion rates, session duration, and engagement with social features—were analyzed alongside semi-structured interviews. Statistical analysis included ANOVA and regression to examine usability and engagement outcomes. The application has continued iterative testing and refinement until May 2025, and it is scheduled for re-launch under the name Wello! in August 2025. Results: Post-implementation UI refinements significantly increased navigation success rates (from 68% to 87%, p = 0.042). ANOVA revealed that movement selection and peer-interaction tasks posed greater cognitive load (p < 0.01). A strong positive correlation was found between digital literacy and task performance (r = 0.68, p < 0.05). Weekly participation increased by 38%, with 81% of participants reporting enhanced social connectedness through group challenges and hybrid peer-led meetups. Despite high satisfaction scores (mean 4.6 ± 0.4), usability challenges remained among low-literacy users, indicating the need for further interface simplification. Conclusions: The findings underscore the potential of hybrid digital platforms tailored to older adults’ physical, cognitive, and social needs. Movement Poomasi demonstrates scalable feasibility and contributes to reducing the digital divide while fostering active aging. Future directions include AI-assisted onboarding, adaptive tutorials, and expanded integration with community care ecosystems to enhance long-term engagement and inclusivity. Full article

This article presents a systematic literature review aimed at identifying challenges and opportunities for integrating sustainability into the digital product lifecycle. The review followed the PRISMA 2020 guidelines and involved a comprehensive search across three databases—Web of Science, Scopus, and ScienceDirect—using structured Boolean queries. A total of 377 records were retrieved, and after duplicate removal and a multi-stage screening process based on predefined inclusion and exclusion criteria, 56 peer-reviewed studies were selected for analysis. These studies were examined in relation to how they addressed environmental, social, and economic dimensions throughout the digital product lifecycle and UX/UI design. Key challenges identified include high energy consumption, limited user awareness of environmental impacts, and the exclusion of vulnerable populations from digital solutions. Opportunities include the adoption of sustainable design strategies, the application of Life Cycle Assessment (LCA), co-design practices, and data-driven decision-making tools. The findings were synthesized into a conceptual framework structured across three lifecycle stages—pre-development, development, and post-development—and mapped to six sustainability requirements. This study contributes to the field by aligning digital innovation with the Sustainable Development Goals (SDGs) and offering a theoretical foundation for the development of practical frameworks and indicators that support sustainable digital product development. Full article

Although smart device use among children is increasing, most interventions overlook their cognitive and emotional development or rely too heavily on external control. Such approaches often overlook the developmental needs of children for emotional regulation and autonomy. Therefore, this study aims to propose a child-centred user experience (UX) framework to support digital self-regulation in preschool-aged children. The proposed system integrates multiple psychological theories—including Piaget’s concept of animistic thinking, executive function theory, Self-Determination Theory, and Acceptance and Commitment Therapy—to support cognitive and emotional regulation during screen use. Key features include persistent visual cues to enhance time awareness and behavioural anticipation, narrative-based character interactions to foster empathy and agency, and ritualised closure routines supported by multimodal and tangible interaction elements. Developed as a mobile prototype, the system was iteratively refined through two-stage consultations with child and adolescent psychiatrists and a developmental psychologist, including formative design feedback and follow-up expert review. Their feedback provided preliminary validation of the system’s developmental validity and emotional coherence. These findings suggest that affectively attuned UX design is a viable alternative to conventional control-based screen-time interventions in early childhood. Full article

This study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI), the Technology–Organization–Environment (TOE), and the Technology Acceptance Model (TAM) combined framework were proposed and tested using data collected from 367 higher education students, faculty members, and employees. SPSS Amos 24 was used for CB-SEM to choose the best-fitting model, which proved more efficient than traditional multiple regression analysis to examine the relationships among the proposed constructs, ensuring model fit and statistical robustness. The findings reveal that Compatibility “C”, Complexity “CX”, User Interface “UX”, Perceived Ease of Use “PEOU”, User Satisfaction “US”, Performance Expectation “PE”, Artificial intelligence “AI” introducing new tools “AINT”, AI Strategic Alignment “AIS”, Availability of Resources “AVR”, Technological Support “TS”, and Facilitating Conditions “FC” significantly impact AI adoption intentions. At the same time, Competitive Pressure “COP” and Government Regulations “GOR” do not. Demographic factors, including major and years of experience, moderated these associations, and there were large differences across educational backgrounds and experience. Full article

Online marketing environments are rapidly being transformed by Artificial Intelligence (AI). This represents the implementation of Machine Learning (ML) that has significant potential in content personalization, enhanced usability, and hyper-targeted marketing, and it will reconfigure how businesses reach and serve customers. This systematic examination of machine learning in the Digital Marketing (DM) industry is also closely examined, focusing on its effect on human–computer interaction (HCI). This research methodically elucidates how machine learning can be applied to the automation of strategies for user engagement that increase user experience (UX) and customer retention, and how to optimize recommendations from consumer behavior. The objective of the present study is to critically analyze the functional and ethical considerations of ML integration in DM and to evaluate its implications on data-driven personalization. Through selected case studies, the investigation also provides empirical evidence of the implications of ML applications on UX/customer loyalty as well as associated ethical aspects. These include algorithmic bias, concerns about the privacy of the data, and the need for greater transparency of ML-based decision-making processes. This research also contributes to the field by delivering actionable, data-driven strategies for marketing professionals and offering them frameworks to deal with the evolving responsibilities and tasks that accompany the introduction of ML technologies into DM. Full article

E-commerce applications have emerged as key drivers of digital transformation, reshaping consumer behavior and driving demand for seamless online transactions. Despite the growth of smart mobile technologies, existing methods rely on fixed UI content that cannot adjust to local cultural preferences and fluctuating user behaviors. This paper explores the combination of generative Artificial Intelligence (AI) technologies with Model-Driven Development (MDD) to enhance personalization, engagement, and adaptability in e-commerce. Unlike static adaptation approaches, generative AI enables real-time, adaptive interactions tailored to individual needs, providing a more engaging and adaptable user experience. The proposed framework follows a three-tier architecture: first, it collects and analyzes user behavior data from UI interactions; second, it leverages MDD to model and personalize user personas and interactions and third, AI techniques, including generative AI and multi-agent reinforcement learning, are applied to refine and optimize UI/UX design. This automation-driven approach uses a multi-agent system to continuously enhance AI-generated layouts. Technical validation demonstrated strong user engagement across diverse platforms and superior performance in UI optimization, achieving an average user satisfaction improvement of 2.3% compared to GAN-based models, 18.6% compared to Bootstrap-based designs, and 11.8% compared to rule-based UI adaptation. These results highlight generative AI-driven MDD tools as a promising tool for e-commerce, enhancing engagement, personalization, and efficiency. Full article

Objectives: This study aims to develop performance indicators for service robotics in senior community-based environments and analyze their impact on independent living and quality of life for older adults. Methods: To achieve this, a sequential exploratory design within the Mixed Methods Research (MMR) framework was employed, integrating qualitative research (Focus Group Interview, FGI) and quantitative research (Analytic Hierarchy Process, AHP). The FGIs were conducted with a panel of six experts over three rounds, leading to the identification of six key performance indicators (KPIs) for service robotics in senior communities: Technical Performance, User-Centered Performance, Social and Psychological Impact, Ethical and Safety Performance, Economic and Operational Performance, and Service Efficiency. Following this, the AHP analysis was conducted with a final sample of 29 participants from an initial 32 respondents. Results: The AHP analysis results revealed that Technical Performance (rank 1, 0.256) was the most critical factor, followed by User-Centered Performance (rank 2, 0.205) and Social and Psychological Impact (rank 3, 0.167). These findings suggest that enhancing a user-friendly, intuitive UI/UX is essential for ensuring ease of use by older adults. Additionally, while Ethical and Safety Performance (rank 3, 0.139), Economic and Operational Performance (rank 4, 0.126), and Service Efficiency (rank 5, 0.105) had relatively lower importance scores, the study highlights the necessity of establishing optimized systems through ethical and safety standards and emphasizes that real-time monitoring systems play a crucial role in enhancing operational efficiency. Conclusions: Enhancing service robotics performance requires prioritizing technical capabilities and user-centered design, along with ethical standards and real-time monitoring. This study proposes a structured evaluation framework to support more effective robotic solutions in senior care environments. Full article

Aligning designer requirements with prototyping platform functionalities remains a challenge in agile development (AD) environments, as existing tools often fail to accommodate evolving needs. This study proposes a systematic approach to optimizing prototyping platforms by bridging the gap between user needs and functional design. First, a designer requirement architecture was constructed using grounded theory, identifying three core elements: interaction needs, collaboration needs, and visualization and testing needs. The F-KANO model was used to categorize requirements, while DEMATEL was used to prioritize them based on interdependencies. Finally, quality function deployment (QFD) was used to map designer needs to functional specifications, deriving an optimization strategy. Empirical evaluation through user testing indicated notable improvements in workflow efficiency, usability, and collaboration effectiveness. This research offers a systematic framework for refining prototyping platforms in AD, improving design efficiency and UX. Full article

Evaluating user experience (UX) is essential for optimizing educational chatbots to enhance learning outcomes and student productivity. This study introduces a novel weighted composite metric integrating interface usability assessment (via the Chatbot Usability Questionnaire, CUQ), engagement measurements (via the User Engagement Scale—Short Form, UES-SF), and objective performance indicators (through error rates and response times), addressing gaps in existing evaluation methods across interaction modes (text-based, menu-based, and hybrid) and question complexities. A 3 × 3 within-subject experimental design (n = 30) was conducted, measuring these distinct UX dimensions through standardized instruments and performance metrics, supplemented by qualitative feedback. Principal Component Analysis (PCA) was used to derive weights for the composite UX metric based on empirical patterns in user interactions. Repeated-measures ANOVA revealed that the hybrid interaction mode outperformed the others, achieving significantly higher usability (F(2,58) = 89.32, p < 0.001) and engagement (F(2,58) = 8.67, p < 0.001), with fewer errors and faster response times under complex query conditions. These findings demonstrate the hybrid mode’s adaptability across question complexities. The proposed framework establishes a standardized method for evaluating educational chatbots, providing actionable insights for interface optimization and sustainable learning tools. Full article

Companies have tried to innovate in their training processes to increase their productivity indicators, reduce equipment maintenance costs, and improve the work environment. The use of Augmented Reality (AR) has been one of the implemented strategies to upgrade training processes, since it optimizes, through User Interface (UI) Design, experiences designed for users (UX) that are focused on education and training contexts. This research describes the definition and implementation of an IT architecture based on the ISO/IEC/IEEE 42010 standard using the Zachman and Kruchten frameworks. The methodological proposal presents an architecture seen from a business perspective, taking into account the strategic and technological components of the organization under a strategic alignment approach. The result is a six-layer architecture: The Government Strategy Layer (1) that accounts for the strategic component; the Business Layer (2) that presents the business management perspective; the Information Layer (4) that defines the metrics system: efficiency through task time, effectiveness through tasks completed, and satisfaction with overall satisfaction. In the Data Layer (4), the data collected with the metrics are structured in an industrial scenario with a cylinder turning process on a Winston Lathe. The experiment was carried out with two groups of 272 participants. In the Systems and Applications Layer (5), two applications were designed: a web client and a mobile application with augmented reality, and finally, the Networks and Infrastructure Layer (6), which delivers the two functional applications. The architecture validation was carried out using the mobile application. The analysis of the results showed a significance value of less than 0.001 in the three indicators: efficiency, effectiveness, and satisfaction in the Levene test and Student’s t-test. To corroborate the results, a test of equality of means with the Mann–Whitney U was carried out, showing that the three indicators presented significantly different values in the two experimental groups of this study. Thus, the group trained with the application obtained better results in the three indicators. The proposed architecture is adaptable to other training contexts. Information, data, and systems and application layers allowed for the exchange of training processes so that the augmented reality application is updated according to the new requirements. Full article

This study introduces an integrative framework for association mining within the Chinese battery electric vehicle market, aiming to reveal key user experience (UX) factors and their interrelationships through multidimensional analysis. Utilizing latent Dirichlet allocation (LDA), the study discerned primary themes from user-generated content (UGC). The entropy weight method categorized level 2 factors, while domain-adaptive sentiment analysis quantified emotional responses to BEV user experience dimensions, highlighting significant sentiment disparities among competitors. Co-occurrence network analysis deepened insights into the emotional fabric of UX by exploring tertiary factor associations. Theoretically, this study advances a novel framework informed by Norman’s UX theory, integrating analytical techniques to capture the complexity of UX. Practically, it delivers strategic guidance for BEV manufacturers by analyzing emotional polarities and attribute associations, guiding product innovation and responding to market dynamics. The empirical evidence corroborates the framework’s efficacy in revealing the emotional associations within BEVUX factors, offering valuable implications for both theoretical development and practical application. Full article

Building on our previous work presented at the Eurographics GCH conference, this paper further explores the characteristics of an “authentic experience”, developing a framework that can be applied to the development of XR and hybrid applications in the field of cultural heritage. While recognising the broader concept of authenticity, we have not focused on an in-depth analysis of it. Instead, we focus specifically on “authentic experiences”. Here, we have extended the definition of authenticity beyond realism or sense of presence, proposing instead a multi-dimensional approach to engaging users cognitively, emotionally, and sensorially (the “Self” dimension) and, at the same time, including two other fundamental dimensions (the “Others” and the “World”) intrinsically connected to the “Self”. We have then further detailed these three dimensions, which are the pillars of the perception of authenticity, identifying their “components” and “elements”. Finally, we transformed the elements into “actionable” design indications, setting the ground to further develop specific design (UI and UX) strategies for digital heritage and serious game applications. Full article

Agile software development prioritizes customer satisfaction through the continuous delivery of valuable software. However, integrating user experience (UX) evaluations into agile projects remains a significant challenge. Existing proposals address specific stages that apply UX evaluation methods but do not fully consider UX artifacts or UX events for integrating user experience into agile processes. To address this gap and support teams, we propose FRAMUX-EV, a framework for evaluating UX in agile software development using Scrum. FRAMUX-EV introduces seven UX artifacts: (1) UX evaluation methods, (2) UX design system, (3) UX personas, (4) UX responsibilities and roles, (5) UX evaluation repository, (6) UX backlog, and (7) UX sprint backlog; and four UX events: (1) pre-planning UX meeting, (2) pre-review UX meeting, (3) weekly UX meeting, and (4) weekly user meeting. The first version of the framework was developed using a seven-step methodology with a qualitative approach. A survey of 34 practitioners validated the usefulness and ease of integration of FRAMUX-EV components, yielding positive results. These findings suggest the potential of FRAMUX-EV as an interesting proposal for integrating UX into agile software development. Full article

This study investigates user experience (UX) sharing behaviors in the context of smartphone user interface (UI) design, emphasizing their significance for UI enhancement and effective marketing strategies. Grounded in the Stimulus–Organism–Response (SOR) framework, we examine how design perception attributes—perceived usability, novelty, enjoyment, and brand image—influence UX sharing, with a spotlight on the mediating role of individual motivation. A quantitative analysis (N = 472), Structural Equation Modeling (SEM), and mediation analysis were conducted. Our findings confirm that these components can positively impact UX sharing by bolstering personal expectations and self-efficacy in knowledge sharing, with perceived usability being an exception as it unexpectedly showed a negative association with sharing frequency. Moreover, perceived brand image and individual self-expectancy and self-efficacy enhance sharing outcomes. This research enriches our understanding of the strategic importance of user interface (UI) design in the context of smartphones, furnishing empirical grounding for devising sustainable UI design strategies and productive marketing tactics. Consequently, it bears considerable relevance to both theoretical insights and practical applications. Full article