Environmental regulation is globally recognized for its crucial role in mitigating environmental pollution and is vital for achieving the Paris Agreement and the United Nations Sustainable Development Goals. There is a current gap in the comprehensive overview of the significance of environmental regulation research, necessitating high-level insights. This paper aims to bridge this gap through an exhaustive bibliometric review of existing environmental regulation research. Employing bibliometric analysis, this study delineates publication trends, identifies leading journals, countries, institutions, and scholars. Utilizing VOSviewer software, we conducted a frequency and centrality analysis of keywords and visualized keyword co-occurrences. This research highlights current hotspots and central themes in the field, including “innovation”, “performance”, “economic growth”, and “pollution”. Further analysis of research trends underscores existing knowledge gaps and potential future research directions. Emerging topics for future investigation in environmental regulation include “financial constraints”, “green finance”, “green credit”, “ESG”, “circular economy”, “labor market”, “political uncertainty”, “digital transformation”, “exports” and “mediating effects”. Additionally, “quasi-natural experiments” and “machine learning” have emerged as cutting-edge research methodologies in this domain. The focus of research is shifting from analyzing the impact of environmental regulation on “innovation” to “green innovation” and from “emissions” to “carbon emissions”. This study provides a comprehensive and structured understanding, thereby guiding subsequent research in this field.

With the rapid increase in electric bicycle (e-bikes) use, the rate of associated traffic accidents has also escalated. Prior studies have extensively examined e-bike riders’ injury risks, yet there is a limited understanding of how their behavior contributes to these accidents. This study aims to explore the relationship between e-bike riders’ risk-taking behaviors and the incidence of traffic accidents, and to propose targeted safety measures based on these insights. Utilizing a mixed-methods approach, this research integrates quantitative data from traffic accident reports and qualitative observations from naturalistic studies. The study employs a binary logistic regression model to analyze risk factors and uses observational data to substantiate the model findings. The analysis reveals that assertive driving behaviors among e-bike riders, such as running red lights and speeding, significantly contribute to the high rate of accidents. Moreover, the lack of protective gear and inadequate safety training are identified as critical factors increasing the risk of severe injuries. The study concludes that comprehensive policy interventions, including stricter enforcement of traffic laws and mandatory safety training for e-bike riders, are essential to mitigate the risks associated with e-bike use. The findings advocate for an integrated approach to urban traffic management that enhances the safety of all road users, particularly vulnerable e-bike riders.

This study explores the influence of digital technologies, including media, on pre-service teachers’ interactions and engagement patterns. It underscores the significance of promoting digital competence to empower pre-service teachers to navigate the digital world responsibly, make informed decisions, and enhance their digital experiences. The objective is to identify key themes and categories in research studies related to pre-service teachers’ digital competence and skill preparations. Conducting a systematic literature review, we searched databases such as SCOPUS, ScienceDirect, and Taylor & Francis, including forty-three articles in the dataset. Applying qualitative content analysis, we identified four major themes: digital literacy, digital competencies, digital skills, and digital thinking. Within each theme, categories and their frequencies were examined. Preliminary findings reveal a growing prevalence of digital competence and literacy articles between 2019 and 2024. The paper concludes by offering recommendations for further research and implementations, with specific criteria used for article selection detailed in the paper. A digital literacy policy for teacher education preparedness is included.

Technological advancements are transforming agriculture, yet adoption rates among agricultural extension officers, especially in regions like West Java, remain modest due to several challenges. This study applies the Technology Acceptance Model (TAM) to investigate factors influencing the adoption of agricultural technologies by agricultural extension officers in West Java. Specifically, we explore the role of socialization, training, access to technology, cost, perceived ease of use, and perceived usefulness in shaping behavioral intention and actual adoption. Data were collected from 295 agricultural extension officers via structured surveys and analyzed using SmartPLS 4 software. The findings indicate that socialization and training collectively enhance both perceived ease of use and perceived usefulness, while Technology Investment Worth specifically enhances perceived usefulness by emphasizing the value of the investment. Access to technology also plays a critical role in increasing ease of use perceptions. Both perceived ease of use and usefulness positively influence behavioral intention, which in turn is a strong predictor of actual adoption. The results provide valuable insights for policymakers aiming to increase technology uptake among agricultural extension officers, promoting sustainable agricultural practices through improved access, support, and cost reduction initiatives.

Air pollution in Jakarta has become a severe concern in the last four months. IQAir, in August 2023, revealed that the level of air pollution had reached 161 points on the Air Pollution Standard Index (APSI). The negative impact on society has placed air pollution as a concern for environmental safety and survival in danger. This condition will encourage the development of a national policy agenda to integrate environmental welfare through various energy efficiency channels. This research analyzes the relationship between air pollutant elements that can reduce air quality. The analysis includes pollutant intensity measured by APSI per unit of pollutant as a measure of efficiency. The aim is to observe energy use, which causes an increase in pollutant levels. This research utilizes dynamic system modeling to produce relationships between parameters to produce factors that cause pollution. The parameters used are motorized vehicles, waste burning in landfills, industry, and power plants. The results of historical behavioral tests and statistical suitability tests show that the behavior is suitable for the short and long term. The simulation results show that the pollution level will worsen by the end of 2027, a hazardous condition for society. The optimistic scenario simulation model proposes immediate counter-measures to reduce pollution to 45.01, the ideal condition. To accelerate improvements in air quality, the Government can plan policies to reduce the use of coal by power plants and industry, as well as the use of electric motorized vehicles, resulting in an ideal reduction in pollution by 2024. In conclusion, pollution can be reduced effectively if the Government firmly implements policies to maintain that air quality remains stable below 50 points.