The study’s objective is to identify the challenges and limitations faced by the current vocational education system in preparing graduates in the era of the industrial revolution in the evolving job market in Tangerang, Indonesia. The study primarily examines vocational high schools and adopts a quantitative and quasi-experimental research approach, using control groups to conduct pre- and posttests. The experimental group experiences demonstrations, whereas the control group receives explanations. Instructors employ a blend of demonstration and explanation techniques to explain equipment operation before allowing students to engage in vocational training. The study, led by students in various engineering fields, evaluates technical competencies, work ethics, and foundational knowledge using tests and observations. Job preparation is assessed using the minimal completeness criteria (MCC), which focuses on the importance of proper knowledge, attitudes, and skills. The results indicate that vocational teachers have the potential to play a pivotal role in introducing cutting-edge, technology-based teaching methods, therefore enabling students to make well-informed decisions about their careers. This research enhances vocational education by incorporating practical skills and attitudes with academic knowledge, effectively addressing the changing requirements of the work market.

The purpose of this study is to examine how financial slack and board gender diversity affect carbon emission disclosure and how that disclosure affects firm value in energy sector companies that are listed on the Indonesian stock exchange between 2017 and 2021. Annual reports and sustainability sources provide secondary data for this quantitative study. Purposive sampling was employed in this investigation, including nine companies and a five-year observation period. Thus, 45 samples altogether were employed in the present study. The partial least squares approach is the data analysis strategy used in this investigation. The study’s findings indicate that the Gender Diversity Board does not significantly affect carbon emission disclosure and significantly influences firm value. Financial slack significantly affects carbon emission disclosure but does not directly affect firm value. Financial slack and board gender diversity through carbon emission disclosure have no significant effect on firm value.

The present study aims at analyzing the various factors influencing consumer attitudes towards the adoption of electric vehicles (EVs) in Saudi Arabia. The study evaluates consumer attitudes, their impact on shaping behaviours, and whether consumer intention mediates the relationship between consumer attitude and purchase behaviour towards EVs. This research employs a mixed-method approach, including literature review, surveys, and data analysis. It investigates EV adoption dimensions encompassing individual, social, economic, and environmental factors. Data collected from 397 current and potential EV owners in Saudi Arabia provide insights into their attitudes and behaviours. Survey findings indicate that in Saudi Arabia, safety rating, social influence, economic value, operating cost, and product variety significantly shape consumer attitudes and influence EV adoption. However, factors like range anxiety, charging infrastructure, environmental concern, and performance expectancy are less significant in affecting consumer attitudes toward EVs and their adoption. Investigating multiple dimensions and employing a mixed-method approach, the study enhances the existing knowledge of consumer attitudes toward EVs in the unique context of Saudi Arabia’s sustainable mobility transition. Policymakers and industry stakeholders can utilize these findings to expedite the shift to sustainable transportation in the Kingdom. This research also guides future investigations in this burgeoning field.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

Immeasurable basic and applied information has been evolved on all important floricultural crops through large-scale worldwide research on interdisciplinary aspects. The quantum and quality of work done on Chrysanthemum, among all other ornamentals, are par excellence. Conscientious attempt has been made to collect the whole multidisciplinary experimental results achieved world over. Despite remarkable achievements in knowledge and technology, a major part of present experimental research on chrysanthemum is largely a routine repeat of work. Assessment of past and present work is now significant for preparing target-oriented future research resolutions. This will help to secure the favored results within a justifiable period.

Static atomic charges affect key ground-state parameters of boron quasi-planar clusters Bn, n ≤ 20, which serve as building blocks of borophenes and other two-dimensional boron-based materials promising for various advanced applications. Assuming that the outer valence shells partial electron density of the constituent B atoms are shared between them proportionally to their coordination numbers, the static atomic charges in small boron planar clusters in the electrically neutral and positively and negatively singly charged states are estimated to be in the ranges of –0.750e (B70) to +0.535e (B200), –0.500e (B7+, B8+, and B9+) to +0.556e (B17+), and –1.000e (B7–) to +0.512e (B20–), respectively.