This study analyzes the dynamic relationships between tourism, gross domestic product (GDP) per capita, exports, imports, and carbon dioxide (CO₂) emissions in five South Asian countries. A VAR-based Granger causality test is performed with time series data from Bangladesh, India, Nepal, Pakistan, and Sri Lanka. According to the results, both bidirectional and unidirectional relationships among tourism, economic growth, and carbon emissions are investigated. Specifically, tourism significantly impacts GDP per capita in Pakistan, Sri Lanka, and Nepal, yet it has no effect in Bangladesh or India. However, the GDP per capita shows a unidirectional relationship with tourism in Bangladesh and India. The unidirectional causal relationship from exports and imports to tourism in the context of India and a bidirectional relationship in the case of Nepal. In Pakistan, it is observed that exports have a one-way influence on tourism. The result of the panel Granger test shows a significant causal association between tourism, economic growth, and trade (import and export) in five South Asian economies. Particularly, there is a bidirectional causal relationship between GDP per capita and tourism, and a significant unidirectional causal relationship from CO₂ emissions, exports, and imports to tourism is explored. The findings of this study are helpful for tourism stakeholders and policymakers in the region to formulate more sustainable and effective tourism strategies.

This study examines the rapid convergence of the tourism industry with other sectors, driven by the expanding experience economy. A conceptual model was introduced encompassing industry convergence patterns, paths, and effects to assess this convergence’s effectiveness. Using a survey of 392 tourists in Macau, these findings reveal that the tourism industry convergence path and mode positively influence the convergence effect, thereby shaping tourists’ perceived value. Moreover, this study identifies that convergence mode and effect mediate the relationship between the tourism industry convergence path and perceived value. This study validates the efficacy of industrial convergence paths and models in fostering regional industry convergence within the tourism sector. Additionally, it contributes a theoretical framework for evaluating industry convergence effects at a micro level, enhancing both the theoretical understanding and practical applications of Macao’s tourism industry and industrial convergence theory.

Dredging and reclamation operations are pivotal aspects of coastal engineering and land development. Within these tasks lie potential hazards for personnel operating dredging machinery and working within reclamation zones. Due to the specialized nature of the work environment, which deviates from conventional workplace settings, the risk of workplace accidents is significantly heightened. The aim of this study is to conduct a comprehensive risk analysis of the safety aspects related to dredging and reclamation activities, with the goal of enhancing safety and minimizing the frequency and severity of potential dangers. This research comprises a thorough risk analysis, integrating meticulous hazard identification from sample projects and literature reviews. It involves risk assessment by gathering insights from experts with direct working experience and aims to assess potential risks. The study focuses on defining effective risk management strategies, exemplified through a case study of a nearshore construction project in Thailand. The study identified numerous high and very high-risk factors in the assessment and analysis of occupational safety in dredging and reclamation work. Consequently, a targeted response was implemented to control and mitigate these risks to an acceptable level. The outcome of this study will provide a significant contribution to the advancement of guidelines and best practices for improving the safety of dredging and reclamation operations.

Recognizing the discipline category of the abstract text is of great significance for automatic text recommendation and knowledge mining. Therefore, this study obtained the abstract text of social science and natural science in the Web of Science 2010-2020, and used the machine learning model SVM and deep learning model TextCNN and SCI-BERT models constructed a discipline classification model. It was found that the SCI-BERT model had the best performance. The precision, recall, and F1 were 86.54%, 86.89%, and 86.71%, respectively, and the F1 is 6.61% and 4.05% higher than SVM and TextCNN. The construction of this model can effectively identify the discipline categories of abstracts, and provide effective support for automatic indexing of subjects.

This paper examines the effect of governance in Sub-Saharan African (SSA) countries. Specifically, this study investigates (i) the interacting impact of government efficiency, regulatory quality, and the rule of law alongside other socioeconomic variables to determine foreign capital inflow (FCI) based on each economic SSA bloc; and (ii) the characteristic drivers of FCI, impacting economic growth in the SSA countries. Descriptive statistics, static models, least square dummy variables (LSDVs) and the dynamic system general method of moment (GMM) were employed as the study’s estimating techniques. Based on the result of the LSDV, food security and the rule of law significantly impact FCI in the sub-economic blocs in the region. Only six countries across the four economic blocs responded to food security and the rule of law in the model. The dynamic system-GMM provided evidence of five socioeconomic variables and three governance variables contributing to FCI. The findings revealed (i) regulatory quality and the rule of law are governance variables that significantly impacted FCI; and (ii) food security failed to significantly impact FCI in the SSA region. However, inflation, life expectancy, the human capital index, exchange rate and gross domestic product (GDP) growth impacted FCI significantly. In the aggregate, inflation, regulatory quality, exchange rate and the human capital index exhibited positive relationships, while other variables such as life expectancy, government effectiveness and the rule of law appeared significant but inversely impacted FCI in the SSA region. The key policy implication recommendation from this study is that a good legal framework could moderate the flow of foreign capital in favour of growth as it creates a strong foundation for sustainable economic development in the region.

African countries have shown interest in developing the legal framework for electronic payment as part of digital law. The article aims to analyze the role of the legal framework for electronic payment in the field of digital economy. It relies on a legal methodology through analyzing legal texts related to electronic payment. It also relies on the comparative and descriptive approaches whenever there is a scientific necessity. The article concluded that the legal framework plays an important role in the field of digital economy. This framework appears in the general rules of civil and commercial laws or through the laws of money and credit. Other laws also play a complementary role, such as criminal law and personal data protection laws.