This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.

Pattaya City is a well-known tourist destination in Thailand, famous for its beautiful beachfront, lively nightlife, and stunning natural scenery. Since 2019, the Eastern Special Development Zone Act, the so-called EEC (Eastern Economic Corridor), has positioned the city as a focal point for Meetings, Incentives, Conferences, and Exhibitions (MICE), boosting its tourism-driven economy. Infrastructure improvements in the region have accelerated urban development over the past decade. However, it is uncertain whether this growth primarily comes from development within existing areas or the expansion of urban boundaries and what direction future growth may take. To investigate this, research using the Cellular Automata-Markov model has been conducted to analyze land use changes and urban growth patterns in Pattaya, using land use data from the Department of Land for 2013 and 2017. The findings suggest an upcoming city expansion along the motorway, indicating that infrastructure improvements could drive rapid urbanization in coastal areas. This urban expansion emphasizes the need for urban management and strategic land use planning in coastal cities.

Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.

Evaluating tourist destinations is extremely important as it is the basis for helping local authorities and the leadership of tourist destinations implement reasonable solutions to strengthen the state management of tourism, encourage investment and upgrade service quality at destinations, better exploit the tourist market, position the tourist destination brand in the international tourism market, increase the length of stay, and increase tourist spending when coming to the tourist destination. The current state of investment and development of tourist destinations means that tourist areas across the country need to be evaluated and classified to have a basis for encouraging investment and strengthening effective management, upgrading service quality at destinations, and gradually positioning the Vietnamese tourism destination brand in the international tourism market. This study evaluates the Ba Na tourist area (Da Nang city, Vietnam) based on the “Set of criteria for evaluating tourist destinations” issued by the Ministry of Culture, Sports and Tourism of Vietnam (2016). issued under Decision No. 4640/QĐ-BVHTTDL on 28 December 2016. Evaluation results show that criteria for tourism resources, landscape, facilities, participation of local communities, and the management of the tourist area are evaluated very well. On the contrary, services for entertainment, shopping, entertainment, and prices of services in the tourist area are limited problems in the Ba Na tourist area.

In recent years, information technology and social media has developed very rapidly and has had an impact on government services to the public. Social media technology is used hugely by several developing countries to provide services, information and promote information disclosure in its government to improve its performance. This study aims to build role of social media technology concept as a public service delivery facilitator to the public. Furthermore, it discusses the potential impact of social media use on government culture. To achieve the goal, this study combines two theories, namely government public value theory and green smart city with four variables, namely quality of public services, user orientation, openness, and greenness. These variables are used as the foundation for data collection through in-depth interviews and group discussion forums. In-depth interviews are utilized as data search and direct observation. The informants consist of several government elements, including heads of regional apparatus organizations, heads of public service malls and Palembang city government employees. The study revealed that the Palembang government has several social media-based public services that have quality of services, user-orientation, openness, and environmental friendliness.

The potential of entrepreneurship to reduce poverty is closely tied to critical factors such as access to finance, training and education, networks and social capital, and supportive regulatory environments. Understanding and addressing these underlying issues through the lens of the Social Capital theory can help foster an entrepreneurial spirit in cities and mitigate poverty through business and community development. This paper explores the insights and standpoints of key stakeholders about poverty in Saint John and its impact on entrepreneurship. The study uses a quantitative method and analyzes data from surveys with stakeholders. The results show that social isolation, system inflexibility, individual issues, housing, and financial support programs are significant poverty challenges in Saint John, and these issues have implications for entrepreneurship. By integrating Social Capital Theory into policy initiatives, policymakers can enhance community resilience and empower vulnerable individuals. This application of social capital principles provides a holistic framework for designing effective poverty-reduction measures, offering transformative insights applicable not only to Saint John but also to diverse small cities. The study contributes a nuanced understanding of poverty’s impact on entrepreneurship, advocating for inclusive strategies that resonate with the social fabric of communities.