Inland Container Depots (ICDs) are inland multi-modal terminals where goods in intermodal loading units can be transferred directly to seaports. The contribution of ICDs to regions’ economic and social growth is undeniable. To achieve the sustainable development of ICDs, evaluating and improving their service quality is critical. This study aims to investigate the factors contributing to the service quality of ICD in a developing country. The data utilized covers some ICDs in the Red River Delta, Vietnam. Regarding analytic methods, descriptive statistics first were run to show the level of aspects of service quality of ICDs. Subsequently, attitudinal statements were analyzed using exploratory factor analysis before linear regression was applied to recognize the factors influencing the service quality of ICDs. Generally, the service quality of ICDs was evaluated at an acceptable level but far from the high one. The results suggested that the four influential service quality factors included location and accessibility, facilities, process and management, and labor. Based on the findings of contributing factors, managerial implications were proposed.

This research analyses the effects of openness, telecommunications, and institutional nexus on economic growth in African countries using a panel model with data from 16 landlocked countries from 1996 to 2021 and employing the pooled mean group estimation technique that mitigates bias from country heterogeneity and discerning short-term and long-term equilibrium dynamics and two-step system-generalized method of moments (GMM) estimation for robustness check. The empirical findings indicate that openness exerts a significantly positive effect on economic growth in the models. This supports the neoclassical model, suggesting that being landlocked should not impede economic growth, but rather, growth should depend on opportunities available to each country. However, institutions and telecommunications show a mixed correlation with economic growth. These findings can guide landlocked developing countries in enhancing their exports and fostering skill acquisition to attract advanced technology. In conclusion, policymakers should improve macroeconomic policies, telecommunications infrastructure, and institutional structure to strengthen the sustainability of economic growth in African landlocked countries.

This research explores the implementation of streamlined licensing frameworks and consolidated procedures for promoting renewable energy generation worldwide. An in-depth analysis of the challenges faced by renewable energy developers and the corresponding solutions was identified through a series of industry interviews. The study aims to shed light on the key barriers encountered during project development and implementation, as well as the strategies employed to overcome these obstacles. By conducting interviews with professionals from the renewable energy sector, the research uncovers a range of common challenges, including complex permitting processes, regulatory uncertainties, grid integration issues, and financial barriers. These challenges often lead to project delays, increased costs, and limited investment opportunities, thereby hindering the growth of renewable energy generation. However, the interviews also reveal various solutions and best practices employed by industry stakeholders to address these challenges effectively. These solutions encompass the implementation of streamlined licensing procedures, such as single licenses and one-stop services, to simplify and expedite the permitting process. Additionally, the development of clear and stable regulatory frameworks, collaboration between public and private entities, and improved grid infrastructure were identified as key strategies to overcome regulatory and grid integration challenges. The research findings highlight the importance of collaborative efforts between policymakers, industry players, and other relevant stakeholders to create an enabling environment for renewable energy development. By incorporating the identified solutions and best practices, policymakers can streamline regulatory processes, foster public-private partnerships, and enhance grid infrastructure, thus catalyzing the growth of renewable energy projects.

This study investigates the role of Chat-GPT with augmented reality applications in enhancing tourism experiences in Thailand, focusing on behavioral intentions and innovation adoption to reduce stress in the tourism industry. The research addresses two key objectives: identifying factors driving consumers' behavioral intentions to adopt AR apps and evaluating the robustness of a modified innovation framework for analyzing these intentions. A conceptual model integrating innovativeness, attitudes, perceived enjoyment, and revisit intentions was developed and tested using Structural Equation Modeling with data from 430 Thai tourists who have one to three years of mobile application experience. The findings highlight that service and technology innovation significantly influence perceived enjoyment and attitude, which in turn mediate the impact on behavioral intention to adopt augmented reality applications. At a significance level of p < 0.001, perceived enjoyment and attitude were identified as critical determinants of BI, underscoring the importance of intrinsic user experiences. Tourists are more likely to adopt augmented reality technologies based on personal perceptions and enjoyment rather than external recommendations. This research provides actionable insights for stakeholders in the tourism technology ecosystem, including technology providers, marketers, and policymakers. By emphasizing the interplay of social, emotional, and hedonic factors in shaping user attitudes, the study introduces a robust framework for advancing augmented reality applications in tourism. The findings underscore the importance of user-centric design to drive technology adoption and offer strategic guidance for developers and entrepreneurs aiming to enhance tourism experiences through innovative augmented reality solutions.

This research aims to identify best practices and policy guidelines that foster sustainable urban ecotourism. As urban areas continue to expand, integrating ecotourism into urban planning emerges as a critical approach to sustainable development. This paper compares the policies and practices of urban ecotourism development in Thailand and China, aiming to construct a sustainable framework applicable to urban ecotourism development. Employing a comparative literature review, this research synthesizes findings from peer-reviewed journals, governmental reports, and case studies published between 2000 and 2024. The analysis focuses on the policies and practices adopted by Thailand and China to promote urban ecotourism, examining their effectiveness, challenges, and outcomes. The review shows distinct approaches in the two countries, with Thailand emphasizing community-based practices and stakeholder involvement and China primarily focusing on top-down policy initiatives for urban ecotourism development. Despite differing strategies, both countries demonstrate a commitment to integrating ecotourism into urban development plans. From the environmental, socio-cultural, and economic three dimensions, key successes include enhanced biodiversity conservation, increased local community participation, and improved tourist satisfaction. Challenges such as inadequate policy implementation, environmental degradation, and the sustainability of ecotourism practices are also discussed. The conclusion is that a holistic approach to urban ecotourism development that aligns policy and practice with the principles of sustainability is meaningful. The proposed framework offers actionable insights for policymakers, urban planners, and ecotourism practitioners aiming to use the potential of ecotourism as a tool for sustainable urban development in Thailand, China, and beyond.

This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.