This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.

Thailand and the EU started negotiating a free trade agreement (FTA) in 2005, but negotiations were subsequently suspended in 2014 after the country’s military coup. The significance of these negotiations are important because of the mutual benefit of achieving higher levels of trade and investment between the world’s largest single market and the second largest ASEAN economy. The Specific Factors (SF) model of production and trade is applied to identify potential winner and loser industries and factors of production in Thailand. The model identifies short-run loses for some labor inputs, return to capital, and output in agriculture and services. In the manufacturing and energy sectors, higher output will benefit some labor inputs and capital owners. Understanding the short-run impact of an FTA could allow policymakers in Thailand to reinforce the institutional infrastructure such as implementing trade adjustment assistance programs (TAA), to help re-train workers who may become unemployed due to free trade.

This research investigates the safety status of water transport in Lake Towuti, South Sulawesi, employing the MICMAC and MACTOR methodologies to discern the factors that affect navigation safety and the interactions among the relevant stakeholders. The MICMAC analysis reveals that the effectiveness of sustainable transportation in Lake Towuti is significantly dependent on technical elements such as vessel certification, maintenance practices, and safety monitoring, alongside robust relationships among key entities like The South Sulawesi Class II Land Transportation Management Center (BPTD), The East Luwu District Transportation Office (Dishub), and the Timampu Port Service Unit (Satpel). When implementing the MICMAC-MACTOR model, it is essential to consider the technical implications of the proposed recommendations from the perspectives of social justice, environmental sustainability, and economic feasibility. The outcomes derived from the MICMAC and MACTOR assessments in Lake Towuti provide critical insights that can be utilized in other lakes across Indonesia, especially those that exhibit deficiencies in safety measures and adherence to inland water transport safety regulations.

This study seeks to explore the information value of financial metrics on corporate sustainability and investigate the moderating effects of institutional shareholders on the association between net cashflows (NCF) and corporate sustainability of the leading ASEAN countries. The dataset consists of companies listed on the Stock Exchange of Thailand, Malaysia and Singapore during 2013–2023. Fixed effects panel regression is executed in this study. Subsequently, the conditional effects served to evaluate the influence of institutional shareholders on the association between NCF and corporate sustainability. This study employs agency theory to explore how the alignment of institutional shareholders influences sustainability outcomes. This study found that institutional shareholders themselves supply information for the sustainability indicator in Thailand and Singapore, but not in Malaysia. Furthermore, adversely correlated with sustainability metrics in all three nations is the interaction term between institutional shareholders and net cashflows. Further investigation reveals that for each nation’s sustainability measures the institutional shareholders offer value relevant to net cashflows at certain amounts. This study not only contributes to existing academic research on sustainability and financial indicators, it also provides practical strategies for companies and investors trying to match financial performance with sustainability goals in a fast-changing global market.

Work can be demanding, imposing challenges that can be detrimental to the job performance of employees. Efforts are therefore underway to develop practices and initiatives that may improve job performance and well-being. These include interventions based on mindfulness, inclusive leadership and work engagement. In the present study, authors have presented an association of inclusive leadership and mindfulness towards job performance through employee work engagement among secondary teachers in the context of Hong Kong. The sample size of 263 teachers working from three secondary schools in Sha Tin, Hong Kong has been incorporated in this study. A structured questionnaire designed on a 5-point Likert scale has been used based on purposive sampling by analysis of IBM SPSS 27 and Smart PLS version 4.0.9 by applying a structural equation modelling approach (SEM). The results indicated a strong positive influence on employee work engagement and job performance. Moreover, the bootstrap investigation showed that mindfulness and inclusive leadership were significantly associated with employees’ work engagement in the presence of mediators’ work engagement. This study adds to the very scarce literature on inclusive leadership and mindfulness. In addition, this research is the first study to test the mindfulness skill, inclusive leadership and job performance relationship. Furthermore, this is the first study to explore the concept of mindfulness and inclusive leadership in the Hong Kong context. Moreover, the findings of this research can be beneficial for future theory development on mindfulness skill and inclusive leadership in cross-cultural contexts.

In the fast-paced modern society, enhancing employees’ professional qualities through training has become crucial for enterprise development. However, training satisfaction remains under-studied, particularly in specialized sectors such as the coal industry. Purpose: This study aims to investigate the impact of personal characteristics, organizational characteristics, and training design on training satisfaction, utilizing Baldwin and Ford’s transfer of training model as the theoretical framework. The study identifies how these factors influence training satisfaction and provides actionable insights for improving training effectiveness in China’s coal industry. Design/Methodology/Approach: A cross-sectional design that allowed the study to capture data at one point in time from a large sample of employees was employed to conduct an online survey involving 251 employees from the Huaibei Mining Group in Anhui Province, China. The survey was administered over three months, capturing a diverse sample with nearly equal gender distribution (51% male, 49% female) and a majority aged between 21 and 40. The participants represented various educational backgrounds, with 52.19% holding an undergraduate degree and most occupying entry-level positions (74.9%), providing a broad workforce representation. Findings: The research indicated that personal traits were the chief predictor of training satisfaction, showing a beta coefficient of 0.585 (95% CI: [0.423, 0.747]). Linear regression modeling indicates that training satisfaction is strongly related to organizational attributes (β = 0.276 with a confidence interval of 95% [0.109, 0.443]). In contrast, training design did not appear to be a strong predictor (β = 0.094, 95% CI: [−0.012, 0.200]). Employee training satisfaction was the principal outcome measure, measured with a 5-point Likert scale. The independent variables covered personal characteristics, organizational characteristics, and training design, all measured through validated items taken from former research. The consistency of the questionnaire from the inside was strong, as Cronbach’s alpha values stood between 0.891 and 0.936. We completed statistical testing using SPSS 27.0, complemented by multiple linear regression, to study the interactions between the variables. Practical implications: This research contributes to the literature by emphasizing the necessity for context-specific training approaches within the coal industry. It highlights the importance of considering personal and organizational characteristics when designing training programs to enhance employee satisfaction. The study suggests further exploration of the multifaceted factors influencing training satisfaction, reinforcing the relevance of Baldwin and Ford’s theoretical model in understanding training effectiveness. Ultimately, the findings provide valuable insights for organizations seeking to improve training outcomes and foster a more engaged workforce. Conclusion: The study concluded that personal and organizational characteristics significantly impact employee training satisfaction in the coal industry, with personal characteristics being the strongest predictor. The beta coefficient for personal characteristics was 0.585, indicating a strong positive relationship. Organizational characteristics also had a positive effect, with a beta coefficient of 0.276. However, training design did not show a significant impact on training satisfaction. These findings highlight the need for coal companies to focus on personal and organizational factors when designing training programs to enhance satisfaction and improve training outcomes.