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:Pakistan is a developing country. Its transportation infrastructure mainly consists of road network. About 95% passengers and fright is transported using the road network. This high demand on road network is because of the unreliable railway system between the cities. Due to such high demand on road network the accident involvement risk of an individual is much high as compared to developed countries. This study uses a new modeling approach to estimate road safety risk for WTP.  A correlated random parameters Tobit model (heterogeneity-in-mean) is integrated with machine learning (Decision tree).  The decision tree categorizes higher-order interactions, while the model captures unobserved correlations and heterogeneity. The framework examines WTP determinants using a representative sample of 3178 road users from Pakistan. The model estimates WTP for different (fatal and severe injury) risk reductions to monetize road traffic crash costs. Results show maximum respondents are willing to support safety improvement policies. The model reveals significant WTP heterogeneity linked to perceptions of road safety and accident risk. Systematic preference heterogeneity emerges through higher-order interactions, offering insights into WTP relationships. Marginal effects highlight varying sensitivities to explanatory variables, quantifying their impact on WTP probability and magnitude. The framework provides two key contributions. It identifies public WTP determinants, emphasizing heterogeneous effects. It also helps in prioritization safety policies by understanding public sensitivity to WTP. The insights further emphasizing on the importance of road safety interventions to the specific socio-economic profiles of road users. This study offers a significant contribution to road safety improvement by providing valuable recommendations for policy makers. By integrating detailed socio-economic factors, it also addresses the urgent need for targeted traffic safety interventions in Pakistan. These findings are expected to aid policymakers and stakeholders in developing effective strategies to enhance road safety and reduce the accident involvement risk effectively.

This research aims to identify risks and determine responses to risks that can affect the implementation of the Bojonegoro Regency Oncology Specialised Hospital Construction Project Phase 2. The research was conducted using literature study and field study methods. Primary data was obtained through documentation, field surveys, and interviews, while secondary data included the Cost Budget Plan (RAB), project schedule, and weekly project reports. Sampling was conducted using the Slovin technique to obtain a representative number of respondents. The results showed that there were 31 relevant risk variables, grouped into 8 categories, namely force majeure, material, equipment, labour, contractual, construction, design and technology, and management risks. Significant risks were identified using the Severity Index method, which measures probability and time impact. The results of the risk analysis using the severity index method showed that there were 24 risks included in the low risk level, 3 risks included in the medium risk level, and 2 risks included in the high risk level.

This research seeks to explore how Part-Time Work and Time Management influence students' academic performance. A quantitative methodology was employed to investigate the relationship between the independent variables, part-time work and time management, and the dependent variable, academic achievement. The study focused on students from Universitas PGRI Wiranegara during the 2021–2024 period who are actively engaged in part-time work. The sample was selected using a probability sampling method, ensuring every student in the population had an equal chance of inclusion. Data collection was conducted through a questionnaire, which underwent validity and reliability testing.  The findings revealed that part-time work significantly affects academic performance, with both positive and negative outcomes, depending on how well students manage their time. Additionally, effective time management proved to be a crucial factor in enhancing academic performance, even when students juggle their time between work and study. Further analysis indicated that both variables collectively have a meaningful impact on academic achievement. This research underscores the critical role of time management skills for students balancing work and study and highlights the importance of institutional support in helping students maintain this balance. 

This study aims to explore the influence of religiosity on depression levels among working women in Indonesia, using data from the Indonesian Family Life Survey (IFLS) 2007-2014. With the increasing participation of women in the workforce, the challenge of maintaining mental health, particularly depression, becomes increasingly relevant. Employing a quantitative approach and logistic regression analysis, this study examines the relationship between religiosity, socioeconomic variables, and depression levels. The results show that religiosity has a significant positive effect on the probability of not experiencing depression, while age, education, and income also exhibit significant positive influences. Conversely, living in urban areas is found to have a significant negative impact. These findings highlight the importance of religiosity and socioeconomic factors in shaping the mental well-being of working women in Indonesia.