Historically, transportation projects and urban mobility policies overlook the dimension of social sustainability, mainly focusing on economic and environmental criteria. This neglect, seen enhanced in the Global South, leads to long travel times, growing congestion, reliance on motorcycles, high traffic accident rates, and limited access to public transport, jobs, and urban facilities, especially for the more vulnerable population. In light of these issues, this paper proposes the Social Sustainability of Urban Mobility (SSUM) approach as an analytical framework that assesses the state of social sustainability in urban mobility by applying a Systematic Literature Review where three gaps were found. First, by tailoring the SSUM approach to the context of the Global South, it is possible to address the population-focused gap in urban mobility. Second, in the literature review, a theoretical gap defining social sustainability in urban mobility and its three primary categories has yet to reach a consensus among practitioners and academics. Finally, more empirical research should be conducted to discuss methodological aspects of operationalizing the SSUM approach through the three main categories: accessibility, the sustainability of the community, and institutionality. The SSUM approach promotes implementing a sustainable urban agenda that builds inclusive, equitable, and just cities in urban mobility.

In today’s fast-paced digital world, generative AI, especially OpenAI’s ChatGPT, has become a game-changing technology with significant effects on education. This study examines public sentiment and discourse surrounding ChatGPT’s role in higher education, as reflected on social media platform X (formerly Twitter). Employing a mixed-methods approach, we conducted a thematic analysis using Leximancer and Voyant Tools and sentiment analysis with SentiStrength on a dataset of 18,763 tweets, subsequently narrowed to 5655 through cleaning and preprocessing. Our findings identified five primary themes: Authenticity, Integrity, Creativity, Productivity, and Research. The sentiment analysis revealed that 46.6% of the tweets expressed positive sentiment, 38.5% were neutral, and 14.8% were negative. The results highlight a general openness to integrating AI in educational contexts, tempered by concerns about academic integrity and ethical considerations. This study underscores the need for ongoing dialogue and ethical frameworks to responsibly navigate AI’s incorporation into education. The insights gained provide a foundation for future research and policy-making, aiming to enhance learning outcomes while safeguarding academic values. Limitations include the focus on English-language tweets, suggesting future research should encompass a broader linguistic and platform scope to capture diverse global perspectives.

The advent of Artificial Intelligence (AI) has transformed Learning Management Systems (LMSs), enabled personalized adaptation and facilitated distance education. This study employs a bibliometric analysis based on PRISMA-2020 to examine the integration of AI in LMSs from an educational perspective. Despite the rapid progress observed in this field, the literature reveals gaps in the effectiveness and acceptance of virtual assistants in educational contexts. Therefore, the objective of this study is to examine research trends on the use of AI in LMSs. The results indicate a quadratic polynomial growth of 99.42%, with the years 2021 and 2015 representing the most significant growth. Thematic references include authors such as Li J and Cavus N, the journal Lecture Notes in Computer Science, and countries such as China and India. The thematic evolution can be observed from topics such as regression analysis to LMS and e-learning. The terms e-learning, ontology, and ant colony optimization are highlighted in the thematic clusters. A temporal analysis reveals that suggestions such as a Cartesian plane and a league table offer a detailed view of the evolution of key terms. This analysis reveals that emerging and growing words such as Learning Style and Learning Management Systems are worthy of further investigation. The development of a future research agenda emerges as a key need to address gaps.

Indonesia, as a maritime country, has many coastal areas with fishing villages that have significant potential, especially in sociological, economic, and environmental aspects, to be developed as models for sustainable development. Indonesia, with its long-standing fishing traditions, showcases the abundant potential and traditional that could help address global challenges such as climate change, rapid urbanization, and environmental and economic issues. This study aims to develop a conceptual model for sustainable cities and communities based on local potential and Wisdom towards the establishment of a Blue Village in the fishing village of Mundu Pesisir, Cirebon, Indonesia. The urgency of this study lies in the importance of developing sustainable strategies to address these challenges in coastal towns. This study involves an interdisciplinary team, including experts in sociology, social welfare, architecture, law, economics, and information technology. Through the identification of local natural and sociocultural resources, as well as the formulation of sustainable development strategies, this study develops a conceptual Blue Village model that can be applied to other coastal villages. The method employed in this study is qualitative descriptive, involving the steps of conducting a literature review, analyzing local potential, organizing focus group discussions, conducting interviews, and finalizing the conceptual model. The study employed, a purposive sampling technique, involving 110 participants. The results of the study include the modeling of a sustainable city and community development based on local potential and Wisdom aimed at creating Blue Villages in Indonesia, and It is expected to make a significant contribution to the creation of competitive and sustainable coastal areas capable of addressing the challenges of climate change and socioeconomic dynamics in the future.

As cities continue to face the increasing demands of urban transportation and the need for sustainable mobility solutions, the integration of intelligent transportation systems (ITS) with smart city infrastructure emerges as a promising approach. This paper presents a novel framework for integrating ITS with smart city infrastructure, aiming to address the challenges of urban transportation and promote sustainable mobility. The framework is developed through a comprehensive literature review, case studies, and stakeholder interviews, providing significant insights into the integration process. Our research outlines the key components of smart city infrastructure that can be integrated with ITS, highlights the benefits of integration, and identifies the challenges and barriers that need to be addressed. Additionally, we propose and apply evaluation methods to assess the effectiveness of ITS integration with smart city infrastructure. The results demonstrate the novelty and significance of this framework, as it significantly reduces traffic congestion, improves air quality, and enhances citizen satisfaction. This paper contributes to the existing literature by providing a comprehensive approach to integrating ITS with smart city infrastructure, offering a transformative solution for urban transportation challenges.

Employee retention promotes positivity in an organization and improves employers’ brand value. As the human resource department operates with the objective of improving employees’ contribution towards the organization, meaningful work is an important topic in the core areas of human resource development (HRD), such as employee involvement, motivation, and personal development. Not only salary, benefits, working environment, and status but also the factors that determine whether you enjoy going to work every day are whether you believe that your work makes a meaningful contribution. In HRD, meaningful work comes to the forefront through a connection with a high level of commitment. Thus, this study aims to establish the relationship between meaningful and purposeful jobs affecting employee retention and the mediating factors of person organization fit (POF) and person job fit (PJF). A cross-sectional study involving a survey methodology was used to collect data from 150 white-collar employees working in the IT, banking, textile, and multinational companies in Bangladesh. The results indicate that job meaningfulness has a positive relationship with employee retention (p-value = 0.031) and both the mediating factors of PJF (p-value = 0.040) and POF (p-value = 0.028). The results also indicate that while POF positively influences employee retention (p-value = 0.019), PJF has no significant influence on employee retention (p-value = 0.164). Thus, promoting employee job meaningfulness and purpose in the workplace may represent an opportunity for organizations to improve employee engagement and retention.