Search Results (1,754)

This paper introduces the Transition Intervention Point System (TIP-System), a Taoist-inspired theoretical framework aimed at supporting sustainability transitions by integrating multidimensional sustainability research by leveraging point theory. The TIP-System consists of 21 Transition Intervention Points (TIPs), each defined by the intersection of five sustainability dimensions (ecological, social, economic, cultural, and inner) with distinct intervention levels (deep and shallow). The TIP-System endeavors to bridge qualitative and quantitative approaches by drawing on cross-cultural insights. It integrates deep interventions—Taoist-inspired meta-coordination, core values, and spiritual-ethical leverage points—with shallow interventions and technical transition pathways, underpinned by continuous adaptive feedback and systemic interdependencies. Preliminary empirical evidence from eight social innovation initiatives and an ongoing EU-funded rural transition project in Southern Europe suggests that the dynamic interplay among the 21 TIPs may facilitate the identification of transition states and support targeted sustainability change. However, the conceptual complexity of the TIP-System also indicates the need for further refinement to improve its practical accessibility. Future research should aim to develop more user-friendly evaluation tools and assess the framework’s performance across diverse contexts. Overall, the TIP-System provides a promising foundation for guiding transformative change across diverse contexts. Although further empirical validation is warranted, the framework’s novel perspective enriches both theoretical inquiry on and the practical application of sustainability transitions. Full article

Teaching social research methodology in university courses, whether qualitative or quantitative, presents significant challenges for both instructors and students. These challenges include the availability of empirical datasets, the illustration of data analysis techniques, the simulation of research report writing, and the facilitation of scenario-based learning. Emerging AI tools, such as ChatGPT-4, offer potential support in higher education, though their effectiveness depends on the context and their integration with traditional didactic methods. This article explores the potential of AI in teaching social research methodology, with a focus on its benefits, limits and ethical considerations. Furthermore, the paper presents a case study of AI application in teaching qualitative research techniques, specifically in the analysis of solicited documents. Generative AI shows the potential to improve the teaching of social research methodology by providing students with opportunities to engage in hands-on learning, interact with realistic datasets and refine their analytical and communication skills. The integration of AI in education should, however, be approached with a critical mindset, ensuring that AI tools serve as a means to sharpen (not replace) traditional methods of learning. Full article

This study aims to investigate a chronological review of the term museum, defined by the International Council of Museums (“ICOM”) and Korean laws, and explore how the museum definitions have been revised historically. Then, it argues how the museum architecture has been spatially changed and explores whether the revised social roles and ethical responsibilities would impact the restructuring of the spatial changes. To this end, it scrutinized new ideas, significant issues, orders of words, and implicit intentions of the museum definitions over time. It analyzed the data of spatial change projects, which were collected through web crawling of the Korean National e-Procurement System. Then, the spatial changes were categorized regarding functions and characteristics. Through an in-depth investigation of a literature review and case studies, the findings suggest that museums had been understood as a place for collecting, exhibiting, and enjoying materials. However, they have been required to play diverse roles, such as collecting, conserving, exhibiting, researching, and communicating heritage for education, reflection, and sharing knowledge over time. However, the issue of cultural enjoyment has come into focus in Korean laws after 2007, and, as a result, spatial changes (e.g., creating immersive experience center, renovating exhibition spaces, and improving convenience spaces) have taken place exclusively in national museums. Thus, it is clear that national museums are aware of the need to actively think about their role with regard to the public and how architecture corresponds to this. Full article

This study investigates the integration of ChatGPT in Philippine higher education institutions (HEIs) through narrative inquiry, employing Clandinin and Connelly’s three-dimensional framework (temporality, sociality, place) to explore the lived experiences of 18 participants (10 students, 8 faculty). The research identifies three global themes: (1) the need for strong ethical guidelines amid widespread but tacit “silent acceptance” of AI use, (2) faculty efforts to adapt traditional pedagogy while addressing concerns about critical thinking erosion, and (3) strategies to optimize ChatGPT’s utility without exacerbating inequities. Participant narratives reveal divergent adoption patterns: urban stakeholders leverage ChatGPT for efficiency and learning augmentation, while rural counterparts face infrastructural barriers that deepen the urban–rural divide. Students report evolving ethical engagement, from initial dependency to reflective use, whereas faculty grapple with academic integrity and assessment redesign. The findings underscore how cultural resistance, institutional policy gaps, and technological disparities shape ChatGPT’s uneven adoption, reinforcing existing educational inequalities. This study contributes to the literature on AI in education by proposing context-sensitive strategies for equitable integration, including offline AI tools for rural areas, faculty training programs, and transparent policy frameworks. By centering stakeholder narratives, the research advocates for culturally grounded AI adoption that balances innovation with pedagogical integrity, offering a model for Global South contexts facing similar challenges. Full article

As urban populations continue to rise, cities face mounting challenges related to infrastructure strain, resource management, and environmental degradation. Sustainable urban development has emerged as a crucial strategy to balance economic growth, social equity, and environmental preservation. In this context, artificial intelligence offers transformative potential, particularly through predictive modeling, which enables data-driven decision making for more efficient and resilient urban planning. This paper explores the role of AI-powered predictive models in supporting sustainable urban development, focusing on key applications such as infrastructure optimization, energy management, environmental monitoring, and climate adaptation. The study reviews current practices and real-world examples, highlighting the benefits of predictive analytics in anticipating urban needs and mitigating future risks. It also discusses significant challenges, including data limitations, algorithmic bias, ethical concerns, and governance issues. The discussion emphasizes the importance of transparent, inclusive, and accountable AI frameworks to ensure equitable outcomes. In addition, the paper presents comparative insights from global smart city initiatives, illustrating how AI and IoT-based strategies are being applied in diverse urban contexts. By examining both the opportunities and limitations of AI in this domain, the paper offers insights into how cities can responsibly harness AI to advance sustainability goals. The findings underscore the need for interdisciplinary collaboration, ethical safeguards, and policy support to unlock AI’s full potential in shaping sustainable, smart cities. Full article

Background: Ensuring the safety of patients in the operating room, through the monitoring and prevention of adverse events is a central priority of healthcare delivery. In the professionalization of operating room nurses, the processes of identifying, assessing, developing, monitoring, and certifying transversal competencies are crucial. While national and international frameworks have attempted to define such competencies, they often vary in scope and remain inconsistently integrated into education and clinical practice. There is, therefore, a need for a comprehensive and structured identification of transversal competencies relevant to both perioperative and perianesthesiological nursing roles. Objectives: To formulate a validated and structured repertoire of transversal competencies demonstrated by operating room nurses in both perioperative and perianesthesiological contexts. Methods: A qualitative descriptive design was adopted, combining shadowed observation with Hierarchical Task Analysis (HTA). A convenience sample of 46 participants was recruited from a university and a public hospital in Italy. Data were collected between September 2021 and June 2023 and analyzed using content analysis and data triangulation. Results: Through a qualitative, inductive and iterative approach the study identified 15 transversal competencies, 50 sub-competencies, and 153 specific tasks and activities. Specifically, operating room nurses working in perioperative and perianesthesiological roles presented the following transversal competencies: communication and interpersonal relationships, situation awareness, teamwork, problem solving and decision-making, self-awareness, coping with stressors, resilience and fatigue management, leadership, coping with emotions, task and time management, ethical and sustainable thinking, adaptation to the context, critical thinking, learning through experiences, and data, information and digital content management. Each competency was associated with specific tasks observed. Conclusions: This framework complements the existing repertoire of technical-specialist competencies by integrating essential transversal competencies. It serves as a valuable tool for the assessment, validation, and certification of competencies related to patient and professional safety, emotional well-being, relational dynamics, and social competencies. The findings underscore the need for academic institutions to revise traditional training models and embed transversal competencies in both undergraduate and postgraduate nursing education. Full article

This article presents a methodological framework for elective surgery scheduling based on the integration of patient-specific Digital Twins (DTs) and reinforcement learning (RL). The proposed approach aims to support the future development of an intelligent e-health platform for dynamic, data-driven prioritization of surgical patients. We generate prioritization scores by modeling clinical, economic, behavioral, and social variables in real time and optimize access through a reinforcement learning engine designed to maximize long-term system performance. The methodology is designed as a modular, transparent, and interoperable digital decision-support architecture aligned with the goals of organizational transformation and equitable healthcare delivery. To validate its potential, we simulate realistic surgical scheduling scenarios using synthetic patient data. Results demonstrate substantial improvements compared withto traditional strategies, including a 55.1% reduction in average wait time, a 41.9% decrease in clinical risk at surgery, a 16.1% increase in OR utilization, and a significant increase in the prioritization of socially vulnerable patients. These findings highlight the value of the proposed framework as a foundation for future smart healthcare platforms that support transparent, adaptive, and ethically aligned decision-making in surgical scheduling. Full article

Objective: This study aimed to explore the emotional, social, and ethical dimensions of early or presymptomatic diagnosis in individuals with Autosomal Dominant Polycystic Kidney Disease (ADPKD). Methods: A total of 118 participants diagnosed with ADPKD were recruited from a tertiary nephrology center in Türkiye. Data were collected via a 22-item structured and open-ended questionnaire. Chi-square and non-parametric statistical tests were used to assess associations between awareness, attitudes, and demographic variables. Results: Although only 10% of participants reported direct disadvantages from their diagnosis, such as difficulties in employment, insurance, or relationships, many voiced concerns about stigma and long-term uncertainties. Genetic awareness was significantly associated with increased likelihood of recommending family screening (p = 0.022), and higher educational attainment correlated with greater disease knowledge (p < 0.01). Despite emotional burden, 71.2% of participants reported adopting lifestyle modifications, and 79.6% expressed willingness to screen their children, though often with ethical hesitation. Conclusions: While early diagnosis of ADPKD may offer clinical benefits, it also introduces complex psychosocial and ethical dilemmas. These findings highlight the importance of integrating patient-centered counseling, clear communication strategies, and supportive policies to ensure informed decision making and mitigate potential harms. Full article

Despite the global integration of generative artificial intelligence (GenAI) tools in higher education, limited research exists on how demographic factors such as gender and academic level shape their adoption and usage, particularly in language learning contexts outside Western settings. This study aimed to fill this gap by examining the usage patterns, satisfaction levels, and acceptance factors of GenAI tools among English major students in Indonesian higher education. Employing a mixed-methods approach, the research collected data from 277 students using surveys and structured interviews to gauge both quantitative and qualitative aspects of GenAI tool utilization. The results indicate ChatGPT, Google Translate, and Grammarly as the most utilized tools for writing assistance, language learning, and research tasks, with consistent satisfaction across demographics. Performance expectancy emerged as the most influential acceptance factor, followed by effort expectancy and facilitating conditions, while social influence played a moderate role. Qualitative findings reveal students rely on GenAI for grammar refinement, translation accuracy, content exploration, and idea generation, reflecting critical and reflective engagement. Nonetheless, concerns about overreliance and ethical implications accentuate the need for balanced integration. These findings inform tailored educational strategies, emphasizing ethical use and fostering critical thinking in GenAI adoption for English language education. Full article

The study of underrepresented ethnic groups in the social sciences is often hindered by structural and epistemic barriers that limit access to culturally embedded knowledge. This article examines the potential of the GPT-4 version of the ChatGPT language model as a complementary research tool used to generate insights into the Merchera ethnic group, whose presence in the academic literature remains minimal and often characterised by misrepresentation. Through a comparative analysis considering ChatGPT responses and the scarce number of existing sources, this study explores the model’s reliability, depth, and limitations. The findings reveal that while ChatGPT offers a coherent synthesis of available knowledge, it tends to reproduce the prevailing biases and informational gaps found in the existing academic discourse. The paper concludes that generative AI may serve as a provisional support for research on marginalised communities, but its outputs must be interpreted with caution and situated within a framework of critical inquiry and ethical responsibility. Full article

This paper introduces the Integrated Model for Sustainable Development (IMSD), a theory-driven governance framework that embeds Corporate Diversity Responsibility (CDR) into climate and energy policy to advance systemic equity, institutional resilience, and inclusive innovation. Grounded in Institutional Theory, the Resource-Based View (RBV), and Intersectionality Theory, IMSD unifies fragmented sustainability efforts across five pillars: Climate Sustainability, Social Sustainability (CDR), Governance Integration, Collaborative Partnerships, and Implementation and Monitoring. Aligned with SDGs 7, 10, and 13, IMSD operationalizes inclusive leadership, anticipatory adaptation, and equity-centered decision-making. It addresses the compounded climate vulnerabilities faced by women and marginalized groups in the Global South, integrating insights from Indigenous resilience and intersectional adaptation strategies. Unlike conventional CSR or ESG models, IMSD institutionalizes diversity as a strategic asset and governance principle. It transforms DEIB from symbolic compliance into a catalyst for ethical leadership, legitimacy, and performance in turbulent environments. The model’s modular structure supports cross-sector scalability, making it a practical tool for organizations seeking to align ESG mandates with climate justice and inclusive innovation. Future empirical validation of the IMSD framework across diverse governance settings will further strengthen its applicability and global relevance. IMSD represents a paradigm shift in sustainability governance—bridging climate action and social equity through theory-based leadership and systemic institutional transformation. Full article

While American magisterial teaching has continuously cast abortion as part of a consistent ethic covering a comprehensive and interrelated set of issues affecting human life and dignity, the teaching also entails a set of tensions between the single issue of abortion and the larger framework, and this has been resolved by insisting that the legality of abortion affects all other issues and so deserves special focus; this focus has played out in public policy with detrimental consequences. This essay argues that if the bishops’ goals truly are a reduction in abortions, the promotion of respect for life and human dignity, and the promulgation of a truly comprehensive and consistent ethic, then there must be a change in their approach. This change would consist of a focus on the unintended lethal impacts of illegality, more grassroots arguments aimed at changing cultural attitudes, and more support—in both rhetoric and action—for measures that work, including but not limited to the myriad levels of structural justice for the poor and women in particular. These actions would, in turn, reinforce the consistent ethic. Further, the bishops should disavow a single-issue approach and move toward an actually comprehensive approach to public policy. Full article

Sustainable marketing emphasizes the integration of social and environmental responsibility into business strategies, positioning employer branding as a vital tool for advancing sustainable organizational practices. Within the healthcare context of Jordan—a country facing unique socio-cultural and systemic challenges—employer branding may foster a culture that promotes safety and employee well-being. While the findings are context-specific, they offer preliminary insights that may be useful in similar healthcare environments in the Middle East or other collectivist settings. This study explores the use of employer branding as a strategic lever to enhance nurses’ safety voice behavior, a critical component of organizational safety and patient care, through the mediating role of employee engagement. Drawing on employer brand theory and self-determination theory, this research investigates how a strong employer brand image contributes to a more engaged nursing workforce, thereby encouraging proactive communication regarding safety concerns. Data were collected from 240 nurses employed at Jordanian hospitals between September and November 2024. The findings reveal that sustainable employer branding—characterized by transparent, ethical, and inclusive organizational values—significantly enhances employee engagement and, in turn, motivates safety voice behavior. By cultivating a supportive work environment that aligns with nurses’ intrinsic motivations, hospitals can improve not only internal communication around safety but also long-term organizational resilience and trust. This aligns with sustainable marketing principles, which advocate for responsible internal stakeholder engagement as part of a broader sustainability agenda. Full article

This article explores the Confucian Classics as foundational texts of rhetorical theory and literary practice (wen ben yu jing 文本于經) in East Asia, arguing that their scriptural authority derives not only from their moral or philosophical content but also from their exemplary literary form. It addresses a scholarly gap concerning the rhetorical dimensions of these texts, especially as interpreted by premodern intellectuals across China, Korea, and Japan. Drawing on case studies of six influential scholars—Liu Xie and Han Yu from Liang and Tang China, Jeong Dojeon and Seong Hyeon from Joseon Korea, and Fujiwara Seika and Ogyū Sorai from Edō Japan—this study examines how each conceptualized and applied rhetorical principles rooted in the Confucian canon. Methodologically, it combines historical, philological, and comparative analysis of primary sources to trace both shared ideals and divergent approaches in their engagement with the Classics. Findings reveal that while these thinkers uniformly upheld the sacred literary status of the Confucian texts, they varied in rhetorical application, corpus selection, and the social and ethical aims of writing. This study concludes that these transnational rhetorical practices constitute a distinct intellectual trend within the Sinographic Cosmopolis, challenging disciplinary boundaries and reaffirming the central role of literary form in the articulation and transmission of Confucian thought. Full article

The rapid growth of digital platforms has fundamentally reshaped network and viral marketing, profoundly transforming how information spreads across social networks and influences consumer behavior. This comprehensive review synthesizes theoretical, computational, and ethical perspectives into an integrated narrative, providing novel insights into the mechanisms driving information diffusion within contemporary interactive marketing. By integrating foundational concepts from social network theory, advanced graph models, and behavioral dynamics, the paper demonstrates how the interplay between network structures, influencer behaviors, and AI-driven algorithms significantly redefines traditional marketing paradigms. A distinctive theoretical contribution of this study lies in its innovative combination of Big Data analytics with AI-based predictive modeling, explicitly revealing how real-time algorithmic personalization not only enhances marketing effectiveness but also creates new ethical tensions surrounding misinformation, algorithmic bias, and consumer vulnerability. Addressing recent calls for greater theoretical originality and narrative coherence in interactive marketing research, this review explicitly highlights how these insights resolve critical theoretical puzzles and clarify contemporary ethical dilemmas. Additionally, the paper identifies emerging trends—including Web3 marketing, decentralized platforms, and neuroscience-driven targeting—offering clear future research directions. Through its integrative, narrative-driven framework, this study significantly advances interactive marketing theory, providing essential guidance for scholars and practitioners navigating the evolving complexities of digital influence. Full article