Poverty, as a phenomenon, remains an obstacle to global sustainable development. Although a universal malaise, it is more prevalent in underdeveloped countries, including Nigeria. However, because of its devastating impacts on the Nigerian economy, such as increasing death rates, high crime rates, insecurity difficulties, threats to national cohesion, and so on, successive administrations have implemented poverty alleviation programs to mitigate the consequences of this disease. Worryingly, despite a multiplicity of projects and massive human and natural resources invested to match global standards, Nigeria remains impoverished. The curiosity at how these programs fail, either because of implementation hiccups or because elites’ wealth and power influence these programs spurred the paper to assess poverty alleviation policies and elitist approaches in Nigeria. The study employed the desk study approach, as it examined secondary sources such as books, journals, articles, and magazines. Its theoretical underpinning was the elite theory. The paper discovered that several factors such as corruption, the elitist nature of the policies which in disguise reflect public interests, lack of continuity, lack of coordination and monitoring system, misappropriation of public resources, and others, led to the poor performances of government in alleviating poverty in Nigeria. The paper concludes that, while the rate of poverty index in Nigeria rises year after year, poverty alleviation efforts in Nigeria have had little or no influence on the Nigerian economy, since most of these projects are purely reflective of the elites’ interests rather than the masses. Therefore, the paper recommends that for there to be a reduction in poverty incidence in Nigeria, a holistic developmental approach should be adopted, the policies formulated and implemented should sync with the needs of the citizens, and quality and viable programs should be sustained and financed irrespective of change in government; public accountability should be instilled; proper coordination and monitoring system should be domesticated, etc.

Nawacita work program of Indonesian Governance aims to actualize a golden Indonesia by 2045 by accelerating development and human resources. However, the Indonesian people face several difficult problems of their own. Several strategic policies have been put into place in Indonesia to promote fair development and lessen regional differences. These policies include macroeconomic management, economic deregulation, the development of new resources economically, the maritime economy, and productivity enhancement. The Nawacita program’s reflection in addressing regional imbalances in Indonesian regencies and cities is covered in this report. This study employs quantitative and bibliographic techniques along with political economic analysis methodologies to investigate in-depth and information. The study’s findings indicate that although differences between Indonesia’s districts and cities are gradually narrowing, the country’s GDP per capita is still below the global average. Most of the strategic measures put in place by the Indonesian Governance have not resulted in the anticipated expansion of the economy. Nonetheless, in current period of government, connectivity in enhancing productivity across regions through Indonesia centric development is a primary objective to ease accessibility between areas, which has frequently been disregarded. particularly in the Papua region, which has not exactly developed and been left behind. According to the Analytical Hierarchy Process (AHP) analysis’s findings, increasing productivity is a task that needs to be finished right now to lessen regional differences in Indonesia.

This study examines the impact of innovation governance and policies on government funding for emerging science and technology sectors in Saudi Arabia, addressing key bureaucratic, regulatory, and cultural barriers. Using a mixed-methods approach, the research integrates qualitative insights from stakeholder interviews with quantitative survey data to provide a comprehensive under-standing of the current innovation landscape. Findings indicate a high level of policy awareness among stakeholders but reveal significant challenges in practical implementation due to bureaucratic inefficiencies and stringent regulations. Cultural barriers, such as a risk-averse mindset and traditional business practices, further impede innovation. Successful initiatives like the National Transformation Program (NTP) demonstrate the potential for well-coordinated efforts, highlighting the importance of regulatory reform and cultural shifts towards entrepreneurship. Strategic recommendations include streamlining bureaucratic processes, enhancing policy coordination, and fostering a culture of innovation through education and stakeholder engagement. This study contributes to the existing literature by offering actionable insights to enhance innovation governance, supporting Saudi Arabia’s Vision 2030 goals.

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.

Rural tourism plays a crucial role in rural development in Indonesia by providing employment opportunities, livelihood, infrastructure, cultural preservation, and environmental preservation. However, it is prone to external shocks such as natural disasters, public health events, and volatility in the national and global economy. This study measures the resilience of rural tourism to external shocks caused by the COVID-19 pandemic in 24 rural tourism destinations in Indonesia covering four years from 2019 to 2022. A synthetic composite index of the Adjusted Mazziotta-Pareto index (AMPI) is used to measure rural tourism resilience followed by clustering analysis to determine the typology of the resilience. The AMPI measure is also compared with the conventional Mazziotta-Pareto index (MPI) method. The resilience index is composed of capacity and performance components related to resilience. The results show that in the first year of COVID-19, most tourism villages in Indonesia were severely affected by the pandemic, yet they were able to recover afterward, as indicated by positive differences in the AMPI index before and after COVID-19. Thus, rural tourism villages in Indonesia have a strong capacity and performance to recover from pandemic shock. Lessons learned from this analysis can be applied to policies related to rural tourism resilience in developing countries.