The rising trend of tourists selecting agrotourism as a tourist destination has become an intriguing study issue. Seremban is a well-known tourist attraction that is popular among visitors. As a result, Seremban has been selected as the study site. However, river pollution may have an influence on Seremban’s natural environment and agrotourism potential. Furthermore, inadequate infrastructure, such as unauthorized parking, exacerbated the inhabitants’ problems. A growing number of young people leave Seremban to pursue employment or further education in other cities, with no desire to work as farmers. The labor scarcity has also made it difficult for farmers to grow their farms. Consequently, the study aims to examine how factors such as the natural environment, tourist infrastructure, perceived social advantages, and perceived barriers influence the attitudes of Seremban residents towards agrotourism, with a focus on its potential for driving economic growth. This study adopts quantitative research methods, employing descriptive and causal research designs. Primary data collection is conducted through questionnaires, supplemented by secondary data. Non-probability quota sampling is utilized due to the absence of a specific sampling frame, with a sample size of 385 respondents determined using G*Power software. Constructs are developed based on previous research, and the questionnaire comprises Likert-scale items to gauge attitudes and perceptions. A pilot study assesses the instrument’s reliability. Data analysis is performed using SPSS software, encompassing multiple linear regression and Pearson correlation analyses in addition to descriptive statistics. The findings provide valuable insights into the factors driving residents’ perceptions of agrotourism in Seremban, emphasizing the importance of the natural environment, tourism infrastructure, perceived social benefits, and perceived barriers in shaping attitudes. Additionally, the study highlights the resilience of residents’ positive attitudes toward agrotourism, despite potential challenges and barriers identified. Overall, these results offer implications for policymakers and stakeholders involved in tourism development in the region.

Access to affordable and quality medicines plays a vital role for achieving Universal Health Coverage and in reducing out-of-pocket expenditures (OOPE) for households especially in developing nations such as India. Pradhan Mantri Bhartiya Janaushadhi Pariyojana (PMBJP), a Government of India initiative, aims to make low-cost and quality generic drugs and surgical equipment accessible to all segments of the population through its dedicated store outlets known as Pradhan Mantri Bhartiya Janaushadhi Kendra (PMBJK). In this study, a pilot survey comprising 20 stores/PMBJKs and 150 citizens was undertaken in the Bengaluru Urban District, India to understand various aspects of the PMBJKs including availability of drugs, stock-outs, accessibility to stores, perception and awareness levels along with challenges faced by store owners and citizens/beneficiaries. Based on the survey results, we capture the availability of drugs for 35 medicines and consumables belonging to 12 therapeutic categories across 20 store outlets. We also provide valuable insights and interdisciplinary recommendations on several facets including adopting technology-based measures for day-to-day functioning of stores, need for in-depth supply chain analysis for ensuring availability of drugs, encouraging prescription of generic medicines, increasing awareness levels in addition to promoting grassroot-level research, surveys and feedback mechanisms. These suggestions are expected to find their utility in policy-making, strengthen the implementation of the PMBJP scheme across Bengaluru and India as well as contribute towards achieving related Sustainable Development Goals.

This research aims to assess the impact of bargaining power on budget implementation while also considering the deviation in capital expenditure as a moderating factor. The research sample included 34 provincial governments in Indonesia between 2019 and 2022. The sample determination method used purposive sampling, so the final sample size was 134 observations. The research employed panel data regression to test the hypotheses and continued with the Chow, Lagrange multiplier, and Hausman tests. The study results indicate that bargaining power has a positive and significant effect on budget implementation, with the deviation in capital expenditure not diminishing its impact. The research’s practical implication is that regional governments must effectively manage their revenues to finance regional spending needs through regional tax intensification and extensification policies. The study contributes to signaling theory by highlighting that regional governments can finance regional spending needs through fiscal independence and society’s involvement. It also contributes to agency theory by demonstrating that capital expenditure deviation in the form of information asymmetry in regional governments does not reduce their ability to finance regional expenditure needs. Nonetheless, the study suggests that the proxies used in this research are limited, and further exploration of other proxies to measure tested variables. This research provides new knowledge for stakeholders regarding the dynamics of regional budgeting, especially regarding assessing the impact of bargaining power on budget implementation and considering deviations in capital expenditure as a moderating factor.

The rise of financial inclusion has notably increased household engagement in risky financial asset allocation, posing challenges to macro-financial stability. This study explored the crucial role of financial literacy in enabling households to effectively engage with complex financial markets and products. Specifically, it examined how different aspects of financial literacy—knowledge, attitudes, and skills—influence both the participation and depth of household investment in risky financial assets in China. Utilizing a comprehensive dataset from the 2019 China Household Finance Survey, which included 32,458 households, this study employed a robust indicator system and regression analysis via STATA 17.0 to assess these impacts. The results demonstrated that enhancements in financial literacy significantly foster increased engagement and deeper involvement in risky asset allocation, particularly through improved financial attitudes. Additionally, the analysis revealed that households led by women show a higher propensity towards risky asset investments than those led by men. These insights suggested the potential for targeted financial education to improve the financial health and economic resilience of Chinese households.

The SMARTER model, an innovative educational framework, is designed for blended learning environments, seamlessly integrating both online and face-to-face instructional components. Employing a flipped classroom methodology, this model ensures an equitable division between online and traditional classroom interactions, aiming to cultivate a dynamic and collaborative learning atmosphere. This research focused on developing and rigorously evaluating the SMARTER model’s validity, practicality, and effectiveness. Adopting a research and development (R&D) approach informed by the methodologies of Borg, Gall, and Gall, this study utilized a mixed-methods strategy. This encompassed a robust validation process by experts in design, content, and media, alongside an empirical analysis of the model’s application in actual educational settings. The aim was to comprehensively assess its effectiveness and practicality. The findings from this study affirm the SMARTER model’s validity, practicality, and effectiveness in improving students’ information literacy skills. Comparative analysis between a control group, taught using a traditional expository approach, and an experimental group, educated under the SMARTER model, highlighted significant improvements in the latter group. This effectiveness underscores the model’s capacity not only to efficiently deliver content but also to actively engage students in a collaborative learning process. The results advocate for the model’s potential broader adoption and adaptation across similar educational contexts. They also establish a foundation for future research aimed at exploring the SMARTER model’s scalability and adaptability across diverse instructional environments.

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.