The government’s increased cigarette tariff aims to lower smoking rates and avoid adverse impacts. This study’s goal was to offer process innovation for lowering Asian’ smoking behavior. The participants were chosen by stratified random selection from a total of 738 people residing in Pathum Thani Province, Thailand. The instrument was a questionnaire. A software programmer was used to examine descriptive and inferential statistics using EFA and one-way ANOVA techniques. A strategic framework guideline using a SWOT analysis and TOWS matrix to encourage smoking reduction was proposed. The findings revealed two components: smoking behavior change and continues smoking that were based on SWOT analysis and TOWs matrix. There were nine strategies for the excise department to consider for the adjustment of the next policy in terms of reducing the number of smokers. The practical and policy suggestions could help reduce the negative impact of the cigarette industry on public health and increase government revenue while addressing weaknesses and threats in the industry.

The rapid shift to online learning during COVID-19 posed challenges for students. This investigation explored these hurdles and suggested effective solutions using mixed methods. By combining a literature review, interviews, surveys, and the analytic hierarchy process (AHP), the study identified five key challenges: lack of practical experience, disruptions in learning environments, condensed assessments, technology and financial constraints, and health and mental well-being concerns. Notably, it found differences in priorities among students across academic years. Freshmen struggled with the absence of hands-on courses, sophomores with workload demands, and upperclassmen with mental health challenges. The research also discussed preferred strategies for resolution, emphasizing independent learning methods, managing distractions, and adjusting assessments. By providing tailored insights, this study aimed to enhance online learning. Governments and universities should support practical work, prioritize student well-being, improve digital infrastructure, adapt assessments, foster innovation, and ensure resilience.

This research quantitatively examines how online professional development (OPD) affects cognitive development in special education instructors. 100 individuals took part in outpatient department activities for six months, undergoing cognitive ability examinations before and after the intervention. Descriptive statistics, paired samples t-tests, multiple regression analysis, analysis of covariance (ANCOVA), and Pearson correlation coefficients were used to analyze the data. The findings show a significant rise in post-test scores on the Cognitive Abilities Test (CAT) after taking part in the OPD program. Years of experience and education level were important indicators of cognitive progress, emphasizing the significance of individual traits. Moreover, those with greater expertise and advanced levels of education often had better marks on the post-test. The results highlight the significance of cognitive growth as a crucial result of professional development for special education instructors, adding to the existing knowledge base. The research suggests giving priority to cognitive growth in professional development programs, customizing programs to meet individual requirements, and offering continuous support to educators. Future studies should investigate how OPD impacts cognitive development and analyze its lasting consequences on teacher efficacy and student results.

There is a growing emphasis on employee engagement in organizations and academia. It is reflected through an increasing number of academic publications that explores the link between human resource management practices and employee engagement. The present study investigates this relationship using bibliometric analysis. It is crucial to understand how human resource management practices influence employee engagement for creating a more productive and engaged workforce. The publications that focused on “human resource management” and “employee engagement” between 1996 and 2023 were analysed using the Biblioshiny package in R from the Web of Science (WoS) database. The analysis examined the existing research trends and also included comparative analysis across different geographic regions. It identified the emerging trends in human resource management research and the interconnectedness of various sub-disciplines within human resource management. This study offers a comprehensive analysis of the relationship between human resource management practices and employee engagement that revealed new avenues for future research and collaboration within the human resource management field. In other words, it will certainly provide valuable insights for future research agendas.

Clustering technics, like k-means and its extended version, fuzzy c-means clustering (FCM) are useful tools for identifying typical behaviours based on various attitudes and responses to well-formulated questionnaires, such as among forensic populations. As more or less standard questionnaires for analyzing aggressive attitudes do exist in the literature, the application of these clustering methods seems to be rather straightforward. Especially, fuzzy clustering may lead to new recognitions, as human behaviour and communication are full of uncertainties, which often do not have a probabilistic nature. In this paper, the cluster analysis of a closed forensic (inmate) population will be presented. The goal of this study was by applying fuzzy c-means clustering to facilitate the wider possibilities of analysis of aggressive behaviour which is treated as a heterogeneous construct resulting in two main phenotypes, premeditated and impulsive aggression. Understanding motives of aggression helps reconstruct possible events, sequences of events and scenarios related to a certain crime, and ultimately, to prevent further crimes from happening.

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.