Climate change is an important factor that must be considered by designers of large infrastructure projects, with its effects anticipated throughout the infrastructure’s useful life. This paper discusses how engineers can address climate change adaptation in design holistically and sustainably. It offers a framework for adaptation in engineering design, focusing on risk evaluation over the entire life cycle. This approach avoids the extremes of inaction and designing for worst-case impacts that may not occur for several decades. The research reviews case studies and best practices from different parts of the world to demonstrate effective design solutions and adjustment measures that contribute to the sustainability and performance of infrastructure. The study highlights the need for interdisciplinary cooperation, sophisticated modeling approaches, and policy interventions for developing robust infrastructure systems.

Over the last few decades, countries in the South have been undergoing rapid urbanization, as if to make up for lost time. Sub-Saharan Africa is characterized by a very low urbanization rate compared to0 the rest of the world. Although the African continent reached its urban transition in 2015, Niger remains by far the least urbanized country, with a rate of 17%. The city of Niamey is the main urban center, with an estimated population of 1,449,801 hbts in 2023, spread over an area of around 33,100 ha. The aim of this study is to analyze the spatial expansion of the city of Niamey from 1984 to 2023. The main data used in this study are raster images from the United States Geological Survey (USGS), vector data from Open Sources Map (OSM) and GoogleEarth, secondary data from the National Institute of Statistics (INS) and field observation. This study enabled us to conclude that between 1984 and 2023, the city of Niamey underwent very strong spatial expansion. The city grew from 4,690 ha to 33,100 ha, i.e. 28,410 ha absorbed in 39 years, with exceptional growth between 2014 and 2023, when the urban area doubled. Its population has risen from 397,437 at the time of the 1988 general population and housing census to an estimated 1,449,801 in 2023 (INS), an increase of 1,052,364 in 35 years. Between these two dates, population density fell from 87.7 to 43.8 inhabitants/km², i.e. half that of 1984. This spatial expansion has resulted in unprecedented peri-urbanization.

In this paper, a study developed at the University of Seniors in Aragón is presented. The Sono-libro, used as an innovative resource, is assessed in the proposal with an educational and pedagogical purpose. The aim is to understand the motivational and learning perception variation after the incorporation of the Sono-libro in the sample. In this quantitative longitudinal design study, the listening habits of the participants are comparatively analyzed at two moments: The first data collection took place before the implementation of the proposal, and the second collection occurred after the proposal. The sample consists of 116 subjects, with 64.16% being women and an average age of 66 years of age. Data was obtained through a validated ad hoc questionnaire judged by experts. The results of the data collections showed an increase in both motivation and perception of the learning obtained, indicating the benefits of incorporating digital resources into contexts of adult students.

Objective: As the scale and importance of official development assistance (ODA) continue to grow, the need to enhance the effectiveness of ODA policies has become more critical than ever before. In this context, it is essential to systematically classify recipient countries and establish tailored ODA policies based on these classifications. The objective of this study is to identify an appropriate methodology for categorizing developing countries using specific criteria, and to apply it to actual data, providing valuable insights for donor countries in formulating future ODA policies. Design/Methodology/Approach: The data used in this study are the basic statistics on the Sustainable Development Goals (SDGs) published annually in the SDGs Report. The analytical method employed is decision tree analysis. Results: The results indicate that the 167 countries analyzed were classified into 10 distinct nodes. The study further limited the scope to the five nodes representing the most disadvantaged developing countries and suggested future directions for aid policies for each of these nodes.

The study investigates the impact of artificial intelligence (AI)-powered chatbots on brand dynamics within the banking sector, focusing on the interrelationships between AI implementation and key brand dimensions, including awareness, equity, image, and loyalty. Using structural equation modeling (SEM) analysis on data collected from 520 banking customers, the study tests eight hypotheses to explore the direct and indirect effects of AI-driven interactions on brand development. The findings reveal that AI chatbots significantly enhance brand awareness in banking services, demonstrating moderate positive effects on both brand equity and brand image. Notably, while brand awareness exerts a strong influence on brand image, it does not have a significant direct effect on brand loyalty. Instead, the study shows that brand loyalty is primarily developed through the mediating effects of brand equity and image, with brand image exerting a particularly strong influence on brand equity. For banking practitioners, these insights suggest a need to integrate AI chatbots within a comprehensive brand strategy that merges technological innovation with traditional relationship-building approaches. Limitations of the study and potential directions for future research are also discussed, providing avenues for further exploration of AI’s role in brand management.

Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.

A significant cohort of Southeast Asian women in Taiwan, having married locals, constitutes a disadvantaged group entangled in the issues of gender, marriage migration, and social class. The lack of human capital, social discrimination and urgent personal economic demands have caused immigrant women in Taiwan to become a source of inexpensive labor in the labor market, they usually prioritize vocational training for employment. Furthermore, the rapidly growing elderly population has resulted in a severe shortage of quality care services in Taiwan. Despite Taiwanese government training for immigrant women, diverse sociocultural factors hinder them from pursuing caregiving professions. Therefore, this study aimed to investigate the effects of care service attendant (CSA) training based on culturally responsive pedagogy (CRP) and design thinking (DT) for immigrant women in Taiwan. Nine Vietnamese and Indonesian immigrant women in Taiwan attended and completed the training. The CSA training comprised core academic modules and practicum modules and was conducted in groups for 170 h over 5 weeks. This study employed a qualitative research approach, gathering data through interviews, observation, and document analysis. The results revealed that CSA training based on CRP and DT was effective in improving immigrant women’s satisfaction with training and their rate of employment as CSAs. Specifically, in addition to basic care service professionalism, the female immigrant trainees developed proactive attitudes toward problem-solving. Moreover, the integration of Taiwanese culture and frequent communication in the training facilitated the self-confidence of these trainees. In the workplace, these female immigrant CSAs’ commitment to meeting clients’ needs and innovating their service boosted the clients’ appreciation and their own cultural competency and empowerment. Overall, this study suggests that the application of CRP and DT in CSA training is a promising way of enhancing the workforce capacity of female immigrant CSAs and has value for low-skilled adult trainees. However, structuring the learning processes clearly and involving instructors with multicultural education and DT education competency are critical to implementing such vocational training.

Rural tourism, which offers authentic cultural and nature-based experiences, is increasingly recognized as a vital tool for sustainable development. Ethiopia, with its rich rural landscapes and cultural heritage, holds immense potential for rural tourism, but the sector remains underdeveloped. This study assesses the facilitating conditions and challenges of rural tourism in Ethiopia using a mixed-methods approach. Results indicate that Ethiopia’s economic growth, improved rural infrastructure, large rural population, higher ethnic and religious diversity index, and 11 UNESCO World Heritage Sites provide strong foundations for rural tourism. However, significant challenges such as inadequate infrastructure, limited marketing, restricted access to financing, ethnic conflicts, environmental degradation, and insufficient stakeholder cooperation hinder its growth. To address these barriers, the study proposes a model encompassing strategic investments in infrastructure, enhancing marketing and promotion, access to finance initiatives, conflict resolution strategies, sustainable tourism practices, enhancing stakeholder coordination, and supportive policy frameworks. By employing these strategies, Ethiopia can harness the full potential of its rural tourism sector, contributing to economic development and community well-being while promoting cultural preservation and environmental sustainability. Also, the proposed model is highly applicable to other developing economies that share similar contexts. Besides, given the importance of the seven fundamental pillars of the model, it remains relevant across tourism types like coastal destinations.