This research investigates the effects of social connectedness, psychological resilience, and post-traumatic stress disorder on the quality of life among those affected by the 2023 Kahramanmaras earthquakes in Türkiye. Surveys were conducted with 207 university students directly or indirectly impacted by the disaster. The relationships between these factors were analyzed using structural equation modeling. The findings indicated that social connectedness had a significant direct effect on psychological resilience, post-traumatic stress disorder, and quality of life. Additionally, psychological resilience negatively influenced post-traumatic stress disorder, while post-traumatic stress disorder had a significant negative effect on quality of life. The analysis also uncovered indirect effects, demonstrating that psychological resilience and post-traumatic stress disorder mediated the link between social connectedness and quality of life. The findings have important implications for disaster recovery efforts, suggesting that interventions should focus on fostering individuals’ sense of belonging by building meaningful relationships for better recovery outcomes.

In this study, changes in the dependence structures of BRICS countries’ stock markets before and after the World Health Organization’s Covid-19 emergency declaration were examined using the time-varying (TV) copula method. The return series of the stock markets were divided into two periods, namely before COVID-19 (BC) and after COVID-19 (AC). The novel time-varying flexy copula (TVFC) proposed in the study provides a more flexible structure and produces better results than the TV single copula and the TV optimal copula in comparative analyses. In addition, risk spillovers between market indices were explored using the CoVaR-Copula method. According to the results, the interdependence coefficients of all countries were higher in the AC period than in the BC period with the exception of the China – South Africa pair. Moreover, the dependence coefficient of India with other BRICS countries was quite high compared to the other pairs. Based on the risk spillover results, it was concluded that the Chinese stock market index was the index least affected by the other BRICS countries in the AC period compared to the BC period.

This study investigates the factors influencing post-traumatic stress disorder in the youth population seven months after the February 6, 2023, Kahramanmaraş earthquakes, which caused massive destruction in Türkiye and resulted in the loss of over 55,000 lives. The effects of gender, damage levels of buildings, financial resources, participation in search and rescue operations, peritraumatic distress, perceived social support, and resilience are investigated for their impacts on post-traumatic stress disorder. The goal is to examine how these factors influence post-traumatic stress disorder not only on average but also across different levels of its distribution. A face-to-face survey was conducted between September and October 2023 with a randomly selected sample of 160 voluntary university students aged 18 and above who had directly experienced the earthquakes in the affected zone. The study employs quantile regression alongside classical regression and conventional statistical methods to examine the effects of various factors on post-traumatic stress disorder. The prevalence rates of PTSD are 65.6 % and 35 % based on the PTSD Checklist for DSM-5 (PCL-5), using cut-off scores of 33 and 47, respectively. Classical regression results indicate that female gender (β = 7.98, p < 0.001), moderate or higher building damage (β = 5.6, p < 0.05), moderate (β = -6.3, p < 0.001) and high (β = -7.69, p < 0.01) financial resources, peritraumatic distress (β = 0.6, p < 0.001), perceived social support (β = -0.12, p < 0.05), and resilience (β = -0.66, p < 0.001) have impacts on average PTSD scores. Quantile regression results reveal that all factors are effective at various quantiles of post-traumatic stress disorder. For instance, while minor damage (β = 5.06, p < 0.05) is found to be significant at the 10th percentile, participation in search and rescue operations (β = 8.12, p < 0.01) is significant at the 80th percentile. The effects of gender, building damage levels, financial resources, peritraumatic distress, perceived social support, and resilience remain consistent, showing no substantial variation across the quantiles of post-traumatic stress disorder. However, in the upper tail of the PTSD distribution, participation in search and rescue operations emerges as a risk factor, exacerbating its severity.

Ensuring sustainability in the global world today depends on perception management as well as financial management. In order to manage the perceptions, which are inherently latent variables as they are measured indirectly through their indicators, they must be accurately handled and modelled comprehensively. In the present study, a hybrid technique combining Bayesian Networks (BN) and Structural Equation Modelling (SEM), which are regarded as causal models, was used to investigate the perceptions of High-Speed Rail System (HSRS) passengers. In order to provide insight into the customer retention strategy for HSRS, the analyses were performed on the survey data gathered from the frequent users of HSRS operating between 2 cities of Turkey. After the measurement model of the perception variables through SEM was established, the relationships between the variables were learned using BN knowledge extraction algorithms. As a result, relationships from image to trust and loyalty, from trust to perceived value, from perceived value to satisfaction, and from satisfaction to loyalty were determined. Final interpretations were made in terms of risk management with the help of the probabilistic predictive ability of the BN by setting evidence on the satisfaction levels of the perceptions.

Public transportation plays a vital role in promoting environmental sustainability and providing convenient transportation for the public. However, individuals with disabilities encounter significant challenges while using public transportation, necessitating an evaluation of their satisfaction levels to address the barriers they face and ensure social equality. Therefore, in this study, a questionnaire survey was conducted on people with disabilities using public bus transportation in Istanbul, Türkiye, and Bayesian network (BN) analysis was used to identify the most relevant factors affecting passenger satisfaction. Based on the findings, increasing bus frequency, improving accessibility, and adequacy of spaces designated for passengers with disabilities, and enhancing security measures are recommended. This study’s contribution lies in introducing a BN model to visualize probabilistic reasoning among factors, offering scenarios to reduce dissatisfaction levels, and identifying key factors affecting passenger satisfaction, demonstrating practical implications. In particular, the results provide a framework that can guide policy makers and transportation providers in translating statistical findings into concrete improvements in accessibility, service reliability, and passenger safety, enhancing the real-world travel experiences of people with disabilities.