Brazil occupies a prominent position as one of the largest domestic air passenger markets globally. In May 2019, OAG Aviation Worldwide Limited (OAG), a renowned global travel data provider, ranked Brazil as the world’s 6th largest domestic market. This study identifies and meticulously analyses statistical trends in how service levels affect passenger demand on domestic air routes in Brazil. To that end, it employs a panel-data gravity model incorporating service as an instrumental variable. The findings confirm the influence of traditional gravity explanatory variables, while also contributing novel insights into the impact of service levels on domestic routes. The analysis reveals that, while factors such as income and distance play a fundamental role in shaping domestic demand, level of service emerges as a crucial determinant on regional connections. Overall, the statistics suggest growing divergences between Brazilian airlines and regional air transport. Accordingly, substantial changes are necessary in both government policies and the services offered by the airline industry in order to harness the full potential of Brazil’s domestic air transport passenger market and foster regional development.

Projects implemented under life cycle contracts have become increasingly common in recent years to ensure the quality of construction and maintenance of energy infrastructure facilities. A key parameter for energy facility construction projects implemented under life cycle contracts is their duration and deadlines. Therefore, the systematic identification, monitoring, and comprehensive assessment of risks affecting the timing of work on the design and construction is an urgent practical task. The purpose of this work is to study the strength of the influence of various risks on the duration of a project implemented on the terms of a life cycle contract. The use of the expert assessment method allows for identifying the most likely risks for the design and construction phases, as well as determining the ranges of deviations from the baseline indicator. Using the obtained expert evaluations, a model reflecting the range and the most probable duration of the design and construction works under the influence of risk events was built by the Monte-Carlo statistical method. The results obtained allow monitoring and promptly detecting deviations in the actual duration of work from the basic deadlines set in the life cycle contract. This will give an opportunity to accurately respond to emerging risks and build a mutually beneficial relationship between the parties to life cycle contracts.

Instability is inherent in global capitalism, impacting all countries, particularly those directly reliant on this economic framework. The USA shapes tourism metrics in dependent nations and influences inbound tourism spending. Using logarithmic models and power tests, the study delineated four dynamic fields (Cn) supporting the thesis of the fusion of tourism and temporary residency. This study demonstrates that tourism and migration correlate with political, economic, and social instability, as evidenced by high statistical correlations. Variance increases during instability, leading to more residency petitions per tourist entry. This pattern is repeated during three major crises: the 2008–2009 financial crisis, the 2011–2013 conflicts in the Middle East and Africa, and the 2016–2017 regional political turmoil and Venezuelan migration. Economic classification tests confirm the association between instability, armed conflict, and heightened tourism and residency tendencies. Tourism income rises steadily, and residency averages increase, especially during periods of regional instability. The study highlights the tight link between tourism and migration with political, economic, and social instability. The statistical analysis reveals significant correlations, showing higher residency pressure during unstable periods. The applied tests confirm that countries in turmoil exhibit heightened tourism and migration tendencies.

This study investigates seismic risk and potential impacts of future earthquakes in the Sunda Strait region, known for its susceptibility to significant seismic events due to the subduction of the Indo-Australian Plate beneath the Eurasian Plate. The aim is to assess the likelihood of major earthquakes, estimate their impact, and propose strategies to mitigate associated risks. The research uses historical seismic data and probabilistic models to forecast earthquakes with magnitudes ranging from 6.0 to 8.2 Mw. The Gutenberg-Richter model helps project potential earthquake occurrences and their impacts. The findings suggest that the probability of a major earthquake could occur as early as 2026–2027, with a more significant event estimated to likely occur around 2031. Economic estimates for a 7.8–8.2 Mw earthquake suggest potential damage of up to USD 1.255 billion with significant loss of life. The study identifies key vulnerabilities, such as inadequate building foundations and ineffective disaster management infrastructure, which could worsen the impact of future seismic events. In conclusion, the research highlights the urgent need for comprehensive seismic risk mitigation strategies. Recommendations include reinforcing infrastructure to comply with seismic standards, implementing advanced early warning systems, and enhancing public education on earthquake preparedness. Additionally, government policies must address these issues by increasing funding for disaster management, enforcing building regulations, and incorporating traditional knowledge into construction practices. These measures are essential to reducing future earthquake impacts and improving community resilience.

A precise risk assessment in a production line constitutes a significant item to identify susceptible areas where there is a possibility of product quality degradation. This also applies to the precast concrete production line in Indonesia that has a spun pile product. Based on a risk assessment activity conducted in this study, it is proposed to build a traceability model in order to maintain and even improve the spun pile product quality in Indonesia. The approach used was the Neural Network of the perceptron model for weighing and will result in a defined traceability path in the context of reducing defects and even failed spun pile products. The simulation result showed that the model has been able to detect risky path possibilities to reduce product quality. The accumulation result of high-risk and medium-risk paths in this study showed that closer to product finalization, the risk will be higher. It is evident that when assessing Indicators, the order from the highest accumulation value first is Curing & Demolding and Stressing & Spinning at 29% each, Casting at 14%, Forming & Setting at 14%, and lastly Cutting & Heading at 14%. Regarding the risk assessment for activities, the first position is Curing & Demolding and Stressing & Spinning with 30% each, the second is Casting and Forming & Setting with 15% each, and the third is Cutting & Heading with 10%.