The COVID-19 pandemic provided a unique opportunity for educators and policymakers to reconsider education systems and rethink what is essential, necessary, and desirable for future generations. A sequential generic qualitative approach was used in this study. Based on the systematic literature review, a content analysis was conducted to identify dimensions that contribute toward higher education institutions sustainability. Subsequently, the Expert Opinion method that involved five professors holding key positions in respective universities from Malaysia, the Netherlands, India, and Bangladesh was applied to propose a post-COVID-19 sustainable framework. Four themes: 1) educational reform; 2) digital transformation; 3) resilience and change management; and 4) sustainability coupled with agility and flexibility formed the framework for HEIs’ sustainability during the post-COVID-19 pandemic. We propose that the themes be examined from an integrated perspective to ensure HEIs can be sustainable in the long run. Finally, other scholars are recommended to conduct a tracer study as well as develop qualitative instruments based on the themes and dimensions identified from the systematic literature review and the Expert Opinion Method to better understand the phenomenon of HEI sustainability.

Given the heavy workload faced by teachers, automatic speaking scoring systems provide essential support. This study aims to consolidate technological configurations of automatic scoring systems for spontaneous L2 English, drawing from literature published between 2014 and 2024. The focus will be on the architecture of the automatic speech recognition model and the scoring model, as well as on features used to evaluate phonological competence, linguistic proficiency, and task completion. By synthesizing these elements, the study seeks to identify potential research areas, as well as provide a foundation for future research and practical applications in software engineering.

Amid the unfolding Fourth Industrial Revolution, the integration of Logistics 4.0 with agribusiness has emerged as a pivotal nexus, harboring potential for transformational change while concurrently presenting multifaceted challenges. Through a meticulous content analysis, this systematic review delves deeply into the existing body of literature, elucidating the profound capacities of Logistics 4.0 in alleviating supply chain disruptions and underscoring its pivotal role in fostering value co-creation within agro-industrial services. The study sheds light on the transformative potential vested within nascent technologies, such as Internet of Things (IoT), Blockchain, and Artificial Intelligence (AI), and their promise in shaping the future landscape of agribusiness. However, the path forward is not without impediments; the research identifies cardinal barriers, most notably the absence of robust governmental policies and a pervasive lack of awareness, which collectively stymie the seamless incorporation of Industry 4.0 technologies within the realm of agribusiness. Significantly, this inquiry also highlights advancements in sustainable supply chain management, drawing attention to pivotal domains including digitalization, evolving labor paradigms, supply chain financing innovations, and heightened commitments to social responsibility. As we stand on the cusp of technological evolution, the study offers a forward-looking perspective, anticipating a subsequent transition towards Industry 5.0, characterized by the advent of hyper-cognitive systems, synergistic robotics, and AI-centric supply chains. In its culmination, the review presents prospective avenues for future research, emphasizing the indispensable need for relentless exploration and pragmatic solutions. This comprehensive synthesis not only sets the stage for future research endeavors but also extends invaluable insights for practitioners, policymakers, and academicians navigating the intricate labyrinthstry of Logistics 4.0 in agribusiness.

The concept of sustainable urban mobility has gained increasing attention in recent years due to the challenges posed by rapid urbanization and environmental degradation. The objective of this study is to explore the role of on-demand transportation in promoting sustainable urban mobility, incorporating insights from customer interests and demands through survey analysis. To fulfill this objective, a mixed-methods approach was employed, combining a systematic literature review with survey analysis of customer interests and demands regarding on-demand transportation services. This study combines a systematic literature review and a targeted survey to provide a comprehensive analysis of sustainable urban mobility, addressing gaps in understanding customer preferences alongside technological and financial considerations. The literature review encompassed various aspects including technological advancements, regulatory frameworks, user preferences, and environmental impacts. The survey analysis involved collecting data on customer preferences, satisfaction levels, and suggestions for improving on-demand transportation services. The findings of the study revealed significant insights into customer interests and demands regarding on-demand transportation services. Analysis of survey data indicated that factors such as convenience, affordability, reliability, and environmental sustainability were key considerations for customers when choosing on-demand transportation options. Additionally, the survey identified specific areas for improvement, including service coverage, accessibility, and integration with existing transportation networks. By providing flexible, efficient, and environmentally friendly transportation options, on-demand services have the potential to reduce congestions, improve air quality, and enhance overall urban livability.

Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.