The fashion industry is one of the largest and fastest-growing sectors of the global economy, with significant social and environmental impacts. However, the prevailing fast-fashion model leads to overconsumption and serious consequences for both the environment and industry workers. In response to this trend, the slow fashion movement has emerged, promoting a more conscious and sustainable approach to clothing production and consumption. This movement involves a variety of practices, including traditional techniques - such as weaving, embroidery, knitting, felting, and dyeing with natural dyes. In this study, a systematic literature review was conducted to explore how traditional techniques are incorporated into contemporary fashion design and production, and whether these techniques truly support local communities. The findings reveal that traditional techniques are linked to sustainability in the fashion industry; however, they require a significant investment of time compared to fast-fashion cycles, resulting in higher production costs. Thus, despite their promising potential, these techniques contradict the prevailing economic model of development followed in the fashion industry. Ultimately, this study highlights the important role of traditional techniques in promoting sustainability and advocates for integrating these practices in the fashion industry through an alternative economic model.

As organizations face increasingly complex and shifting stakeholder landscapes, innovative methods are needed to identify and engage with both present and future stakeholders. This article explores the integration of participatory and speculative design approaches for stakeholder identification. Our case study was conducted within an international organization focused on intellectual property protection, and it addressed a critical organizational task: Identifying actual and potential stakeholders. Traditional top-down approaches to stakeholder identification were found to be limiting due to the evolving nature of stakeholder relationships. Therefore, we proposed a design-led approach that involved participatory workshops and speculative thinking, empowering the organization to maintain a dynamic stakeholder list in the future. The project involved interviews with key staff, participatory workshops to identify and prioritize values, and a speculative approach - the Stakeholder Mapping Cone - to identify stakeholders and predict their future impact. By combining the creativity of speculative design with the inclusivity of participatory methods, the project allowed the organization to identify existing stakeholders and envision potential future stakeholders. This research demonstrates that speculative and participatory design are viable methods for stakeholder identification, offering innovative approaches that challenge conventional strategies and empower organizations to adapt to future challenges. It also introduces the need to explore how speculative design can evolve into operative speculative design thinking.

Many chatbots fail to meet user expectations and are often perceived as not useful due to design, technical, and usability shortcomings. Usability is a critical factor in the design of effective chatbots because it ensures that users can achieve their goals efficiently, effectively, and satisfactorily. A chatbot with high usability enhances the user experience (UX), builds trust, and promotes engagement. UX also plays a pivotal role in the design of effective chatbots, as it directly influences user satisfaction, engagement, and the overall success of interactions. Both usability and UX are critical factors in the design of effective chatbots, as they influence how easily and satisfactorily users can interact with the system. Activity theory provides a robust framework for understanding and designing usability for effective chatbots by focusing on human activities, the tools mediating these activities, and the context in which they occur. It also provides a structured approach for designing UXs by focusing on the interaction between users, tools (e.g., chatbots), and their environment. This paper describes how activity theory has been used to design a road sign chatbot that offers information on road signs in Malaysia to road users. The Road Sign Chatbot was evaluated through a User Acceptance Test and the results revealed that users found the system is user-friendly, satisfactory, and enjoyable to use.

Initiatives like carbon credits are not sufficient for addressing climate change, particularly if reliance is placed solely on corporations. This study proposes a grassroots initiative in which new automobile buyers join a club that fosters conscious environmental responsibilities through a symbolic declaration of their commitment, and also creating a personal identity. The suggested approach will not only create new sustainable values but also enhance the quality of life by supporting integration into emerging environmental ecosystems of consumption and production. By embedding persuasion using behavioral economics, these changes can be achieved by nudging fossil fuel car buyers using creative marketing strategies and well-designed, recognizable products.

Urban waterfront green spaces are key elements in the urban framework, enhancing city livability. Centered around water bodies, they often form the most vibrant open spaces in cities. They offer people leisure, entertainment, fitness, and other diversified activities, enriching the cultural life of citizens. In addition, developing waterfront green spaces helps enhance a city’s image and foster residents’ sense of belonging and pride. At present, there is limited research on evaluating the recreational suitability of urban waterfront green spaces. This study aims to establish an evaluation system for recreational suitability tailored for Linyi’s waterfront green spaces. The Delphi method and analytic hierarchy process were employed to screen evaluation indicators and determine their weights, constructing the evaluation system. The evaluation standards were clarified, and Linyi Calligraphy Square was evaluated as an example. Data were gathered through questionnaires, on-site surveys, and reviews. The fuzzy comprehensive evaluation method showed that the recreational suitability score of Linyi Calligraphy Square is 4.004, indicating a high level of recreational suitability. Among these, the evaluation results rated the facility (0.42), recreational experience (0.484), and location and transportation (0.375) as “very good,” the environment (0.503) and landscape (0.391) as “good,” and the resources (0.439) as “average.” Based on these results, suggestions were made for Linyi Calligraphy Square, including increasing children’s activity facilities and venues, strengthening safety measures for water-related recreation, and providing reasonable and effective references for future development and construction.

Technology has transformed the field of interior design, improving efficiency through the use of digital tools. However, calculating building codes remains a complex, time-consuming, and error-prone task. Mobile apps have demonstrated their ability to facilitate complex tasks such as calculating clinical scoring systems and medication dosage in the medical field. Despite this potential, user-friendly solutions for building code compliance remain limited. Therefore, this study aims to explore the experiences and challenges faced by design professionals when working with building codes and to assess their willingness to adopt a new mobile app designed to help with building code calculations. Using a mixed-methods approach, 31 participants from the Midwest and South Central regions, including industry professionals and instructors, were interviewed about their experience with building codes. Participants were then introduced to the Building Code Calculator (BCC) app and surveyed using the innovation diffusion theory framework. The interviews revealed that professionals and students experience challenges with the current available resources and traditional calculation methods. Professionals also recognize the potential of the BCC app in improving efficiency and enhancing students’ learning. Survey results indicated strong agreement among instructors regarding the app’s relative advantage, image, ease of use, result demonstrability, visibility, and trialability, indicating a high willingness to adopt the tool. In addition, statistical analysis using the one-sample Wilcoxon test suggested a significant difference between the observed median and the hypothesized median for all survey questions. These findings suggest that the BCC app can potentially enhance efficiency in professional practice and serve as a teaching aid in classroom settings.

Alzheimer’s disease (AD) represents a significant global health challenge, affecting millions of individuals worldwide through progressive cognitive decline and behavioral changes. The burden extends beyond patients to caregivers and healthcare systems. While traditional diagnostic methods pose financial obstacles, emerging non-imaging techniques show promise. Machine learning has emerged as a transformative approach for enhancing both diagnosis and management. This study aims to develop a robust multi-class classification model using random forest (RF) and extreme gradient boosting algorithms on non-imaging data from the Australian AD Neuroimaging Initiative, with emphasis on the Australian Imaging, Biomarkers, and Lifestyle Study of Aging. Extensive data analysis was conducted, including feature importance and selection, to improve interpretability and classification accuracy. Synthetic oversampling was applied to address class imbalance. The findings indicate the superiority of the tuned RF model, achieving 90% in accuracy, precision, recall, and F1 scores. In addition, cost-effective diagnostic variables were explored, with neuropsychology assessment variables demonstrating exceptional accuracy (90%). This research contributes to early AD detection, personalized treatment, and optimized resource allocation.