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Advanced Technologies for User-Centered Design and User Experience: 2nd Edition
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Advanced Technologies for User-Centered Design and User Experience: 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 1599

Special Issue Editors

Dr. Ilsun Rhiu

E-Mail Website
Guest Editor
Division of Future Convergence (HCI Science Major), Dongduk Women's University, Seoul 02748, Republic of Korea
Interests: HCI (human-computer interaction); UX (user experience); UCD (user-centered design); ergonomic design
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Myung Hwan Yun

E-Mail Website
Guest Editor
Department of Industrial Engineering, Seoul National University, Seoul 08826, Republic of Korea
Interests: ergonomics; human factors; user-centered design; human interface design; affective engineering; Kansei engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With recent technological advances, high-tech products that work with users through various methods such as tactile interfaces, gesture recognition, voice commands, and motion detection are increasing. They include innovative technologies ranging from smart devices to AI speakers, virtual reality systems, and augmented reality devices, but the increase in these products has raised concerns about user inconvenience due to the lack of consideration of user needs and behavior for design.

This journal covers all topics studied from user experience (UX) and user-centric design (UCD) perspectives in the context of new high-tech products, devices, and services and interactions between users. This Special Issue welcomes original, unpublished research contributions including, but not limited to, methodological studies and quantitative, qualitative, or mixed-methods studies focusing on issues around consumer interactions with new technologies or methodologies.

In detail, this Special Issue includes the following research topics:

  • New user-centered design methodologies;
  • Design and evaluation of high-tech products or smart products;
  • New methodologies for gathering user experience data;
  • New methodologies for evaluating user experience;
  • User experience design for high-tech products or smart products;
  • Review articles related to UCD/UX methodologies and their challenges.

Dr. Ilsun Rhiu
Prof. Dr. Myung Hwan Yun
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • user-centered design
  • user experience
  • usability
  • human–computer interaction
  • smart products/applications

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Related Special Issue

Published Papers (3 papers)

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Research

29 pages, 13423 KiB  
Article
Deep Learning-Based Imagery Style Evaluation for Cross-Category Industrial Product Forms
by Jianmin Zhang, Yuliang Li, Mingxing Zhou and Sixuan Chu
Appl. Sci. 2025, 15(11), 6061; https://doi.org/10.3390/app15116061 - 28 May 2025
Viewed by 200
Abstract
The evaluation of imagery style in industrial product design is inherently subjective, making it difficult for designers to accurately capture user preferences. This ambiguity often results in suboptimal market positioning and design decisions. Existing methods, primarily limited to single product categories, rely on [...] Read more.
The evaluation of imagery style in industrial product design is inherently subjective, making it difficult for designers to accurately capture user preferences. This ambiguity often results in suboptimal market positioning and design decisions. Existing methods, primarily limited to single product categories, rely on labor-intensive user surveys and computationally expensive data processing techniques, thus failing to support cross-category collaboration. To address this, we propose an Imagery Style Evaluation (ISE) method that enables rapid, objective, and intelligent assessment of imagery styles across diverse industrial product forms, assisting designers in better capturing user preferences. By combining Kansei Engineering (KE) theory with four key visual morphological features—contour lines, edge transition angles, visual directions and visual curvature—we define six representative style paradigms: Naturalness, Technology, Toughness, Steadiness, Softness, and Dynamism (NTTSSD), enabling quantification of the mapping between product features and user preferences. A deep learning-based ISE architecture was constructed by integrating the NTTSSD paradigms into an enhanced YOLOv5 network with a Convolutional Block Attention Module (CBAM) and semantic feature fusion, enabling effective learning of morphological style features. Experimental results show the method improves mean average precision (mAP) by 1.4% over state-of-the-art baselines across 20 product categories. Validation on 40 product types confirms strong cross-category generalization with a root mean square error (RMSE) of 0.26. Visualization through feature maps and Gradient-weighted Class Activation Mapping (Grad-CAM) further verifies the accuracy and interpretability of the ISE model. This research provides a robust framework for cross-category industrial product style evaluation, enhancing design efficiency and shortening development cycles. Full article
(This article belongs to the Special Issue Advanced Technologies for User-Centered Design and User Experience: 2nd Edition)
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17 pages, 1083 KiB  
Article
Advancing Workplace Efficiency: A Motivated Information Management-Based Model for Information Consumer Experience
by María Paz Godoy, Cristian Rusu, Toni Granollers, Fuad Hatibovic and Luisa König
Appl. Sci. 2025, 15(10), 5707; https://doi.org/10.3390/app15105707 - 20 May 2025
Viewed by 260
Abstract
The Information Consumer Experience (ICX) significantly impacts organizational performance. ICX is influenced by three key dimensions: personal, social, and organizational. However, no studies have provided a solid theoretical foundation for ICX. This study presents a theoretical model that integrates these dimensions within the [...] Read more.
The Information Consumer Experience (ICX) significantly impacts organizational performance. ICX is influenced by three key dimensions: personal, social, and organizational. However, no studies have provided a solid theoretical foundation for ICX. This study presents a theoretical model that integrates these dimensions within the Theory of Motivated Information Management (TMIM) to offer a comprehensive framework for understanding and analyzing ICX in organizations. The proposed model combines personal, social, and organizational factors within the TMIM framework, providing a holistic view of how information consumption affects employee performance and organizational outcomes. It emphasizes individual cognitive and emotional responses, as well as the broader organizational context in which information is managed and shared. Our findings show that incorporating these dimensions into the TMIM framework strengthens the model, addressing TMIM’s limitations and providing a more robust approach to ICX. Specifically, the inclusion of emotional factors beyond anxiety, the role of social interactions and organizational culture, and the impact of organizational structures and technology policies enriches the model. These findings suggest that optimizing information consumption through improved management can enhance organizational efficiency, employee satisfaction, and overall performance. This model fills a gap in the literature, offering a theoretical basis for future ICX research and empirical exploration of the interaction between these dimensions in organizational contexts. Full article
(This article belongs to the Special Issue Advanced Technologies for User-Centered Design and User Experience: 2nd Edition)
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27 pages, 4637 KiB  
Article
Artificial Empathy in Home Service Agents: A Conceptual Framework and Typology of Empathic Human–Agent Interactions
by Joohyun Lee and Hyo-Jin Kang
Appl. Sci. 2025, 15(6), 3096; https://doi.org/10.3390/app15063096 - 12 Mar 2025
Viewed by 715
Abstract
As artificial intelligence (AI) technology advances, there has been a diversification of home service functions and services, as well as a change in the applied technologies and functions. This is due to the fact that the needs and expectations vary depending on the [...] Read more.
As artificial intelligence (AI) technology advances, there has been a diversification of home service functions and services, as well as a change in the applied technologies and functions. This is due to the fact that the needs and expectations vary depending on the purpose of performing the task in the same environment. Although interactions with AI often occur in the home environment, which is a personal space, there is a need for research that examines interactions in consideration of the concept of empathy. This study thus aims to identify previous studies that examine the interaction between users and technology and to systematize the elements of interaction that can be considered based on intelligent agents that are often used in the home environment. To this end, a framework was established to examine multifaceted elements through research that shows that the interaction between technology and users should be natural, with sophisticated psychological anthropomorphism. This study analyzed the literature for the establishment of an artificial empathy interaction system and presented an initial framework. Subsequently, we proceeded to the application of authentic industry cases to the framework, with the objective of ascertaining the feasibility of mapping groups exhibiting analogous trends. This process culminated in the categorization of these cases into three distinct types, alongside the identification of the empathy interaction elements that should be given consideration for each category. Moreover, we identified additional components necessary for the formulation of the final framework and elements that were deemed to be superfluous. Thereafter, we initiated the refinement process to elaborate the framework. The final framework is “Empathic HAX (human-agent interactions) Canvas”, which is designed to examine the necessity of empathic interaction between users and AI agents in the home service domain and to determine the optimal design for such interaction. The significance of this study lies in the creation of a framework that has not previously existed, and the presentation of a design tool that is highly likely to be used both academically and practically. Full article
(This article belongs to the Special Issue Advanced Technologies for User-Centered Design and User Experience: 2nd Edition)
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