This study examines the contentment and commitment of rural residents from three different perspectives. The first is environmental management, followed by municipal services and finally territorial planning. The study’s objective is to analyze the causal relationships between the expected quality and perceived quality concerning perceived value, satisfaction and citizen loyalty to provide tools for decision-making to public managers. This research proposes a structural equation model to evaluate and validate five hypotheses. For this study, household-level surveys were implemented to a population sample of 450 families in the rural area of Tenguel in Ecuador. The results suggest that the public policies exercised by territorial managers significantly influence citizens’ perceived value, satisfaction, and loyalty, which impacts social welfare. This research shows that there are deficient areas that negatively impact perceived locality, which decreases the perceived value. Such as firefighting service, municipal police, veterinary services, preservation of historical and cultural assets and activities, and facilities for community use.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

The objectives of the study are to assess the impact of green human resources management (GHRM) policies and knowledge on the environmental performance of a public transportation company employees. Data from 1130 respondents were analyzed using SmartPLS modeling. The findings that GRHM affected employees of a public transportation company mediated by roles of green human resources management policies and knowledge. GRHM affected public transportation employees’ environmental performance significantly. Employees in the public transportation industry can use the study’s results to their advantage by developing plans to increase their sense of belonging to the company and their impact on the environment. Therefore, many companies understand the value of public transportation employees as the forefront ‘agent of change’ towards a significant positive environmental change in the community.

The R3A Route represents a collaborative initiative involving the governments of Thailand, Laos, and China aimed at bolstering connectivity along the North-South Economic Corridor, as a vital component of the Greater Mekong Subregion Economic Cooperation Program (GMS). Since its inception in 2008, this endeavor has substantially enhanced the logistical framework between Thailand, Laos, and China. However, it has also revealed an imbalance in the benefit distribution of value chains within the tourism industry. One of the fact that, local stakeholders in each country often leverage their home country’s advantages, leading to the exploitation of counterparts with lower capacity in other nations. This unfair utilization goes against the initial intentions of fostering collaboration among these countries. Given China and its development as a starting point for tourism and its popularity among tourists traveling this route, this study provides a comprehensive analysis of China’s policy and insights of its influences on R3A tourism development in Laos and Thailand. The study constructs a content analysis with an umbrella of stakeholder analysis based on reliable data and is cross-verified through data triangulation. The findings lead to recommendations aimed at making Thai-Lao-Chinese tourism cooperation more sustainable and effective.

The Malaysian dilemma presents a complex challenge in the wake of the COVID-19 pandemic, requiring a comprehensive statistical analysis for the formulation of a sustainable economic framework. This study delves into the multifaceted aspects of reconstructing Malaysia’s economy post-COVID-19, employing a data-driven approach to navigate the intricacies of the nation’s economic landscape. The research focuses on key statistical indicators, including GDP growth, unemployment rates, and inflation, to assess the immediate and long-term impacts of the pandemic. Additionally, it examines the effectiveness of government interventions and stimulus packages in mitigating economic downturns and fostering recovery. A comparative analysis with pre-pandemic data provides valuable insights into the extent of economic resilience and identifies sectors that require targeted support for sustained growth. Furthermore, the study explores the role of technology and digital transformation in building a resilient economy, considering the accelerated shift towards remote work and digital transactions during the pandemic. The analysis incorporates data on technological adoption rates, digital infrastructure development, and innovation ecosystems to gauge their contributions to economic sustainability. Addressing the Malaysian Dilemma also involves an examination of social and environmental dimensions. The study investigates the impact of economic policies on income distribution, social equity, and environmental sustainability, aiming to achieve sustainable economic growth. The study contributes a nuanced analysis to guide policymakers and stakeholders in constructing a sustainable post-COVID-19 economy in Malaysia.