Economic Sciences

The research attempts to address the research problem, which focuses on the fact that the significant technological developments in the global oil industry lead to a technological gap between the oil companies and the national oil companies in the Gulf Cooperation Council (GCC) countries if these developments are not kept pace. This has prompted these countries to seek to leverage artificial intelligence technology to exploit their oil wealth and maintain their position in the international oil market. Research objective: The research aims to shed light on the concept of artificial intelligence and its impact on the oil sector. Artificial intelligence has led to a major technological leap in the oil industry. Given that the Gulf Cooperation Council countries rely primarily on the oil industry, and that oil represents a strategic international commodity on which all countries of the world continually rely, the GCC countries must keep pace with the latest developments in this field to achieve an appropriate return and ensure their position in the oil market commensurate with their large reserves and the subsequent development of the oil industry. The research hypothesis addresses the following: Artificial intelligence technology employed in the oil industry has proven successful in oil-producing companies, including the Gulf Cooperation Council (GCC) countries, where it has increased recovery rates, increased proven oil reserves, and reduced the cost of production and oil operations compared to the use of traditional methods. Research Structure: To prove the research hypothesis, the research was divided into three sections. The first addressed the theoretical framework of artificial intelligence, the second focused on the areas of artificial intelligence use in the oil sector, and the third addressed its uses in the Gulf oil industry and its economic impacts. The research concluded with the most important conclusions and recommendations

The research aimed to identify the effect of management by wandering around in improving the level of performance through education. To achieve this research was conducted on a random sample of (48)item. The statistical package for social sciences(SPSS)was used to analyze and examine the hypotheses. The researcher used many statistical methods to achieve the research objectives, such as regression. The essential problem of this research by the main question: What is the impact of management by wandering around in improving the level of performance through education? The results showed a statistically significant effect between management by wandering around and the level of performance improvement through education. The research also presented a number of recommendations, the most important of which are: urging managers at supervisors levels to activate the practice of management by wandering around in its dimensions in the organization, and granting authority to department and division managers to provide tangible and intangible incentives to improve the performance of employees

The study primarily aimed to determine the importance of intellectual curiosity in promoting strategic excellence. Intellectual curiosity was measured through its dimensions (knowledge seeking, pleasurable exploration, social curiosity, stress tolerance, and thrill seeking), while strategic excellence was measured through its dimensions (areas of influence, competitive structure, and competitive pressure). A descriptive-analytical approach was followed to present, interpret, and analyze the study data. A questionnaire was used as a tool to collect data and information, with the study sample consisting of (322) employees. A number of descriptive statistical measures (Pearson's correlation coefficient) and structural equation modeling (SEM) were also used. The study concluded that intellectual curiosity at the field level plays a significant role in achieving strategic excellence. Therefore, one of the study's most important recommendations was to encourage employees to learn and provide all the means that facilitate this to enhance thinking and add value to their performance.

This study aims to use artificial intelligence techniques, specifically machine learning, to predict stock prices for a sample of companies in the banking, hotel and tourism, and industrial sectors of the Iraq Stock Exchange. The study will be conducted over two timeframes: the first from March 2015 to March 2025, and the second from April 2025 to December 2027. The study's primary hypothesis is the accuracy of stock price predictions using machine learning. This was achieved using specialized statistical software MATLAB. The study reached several conclusions, most notably the accuracy of machine learning in predicting the stock prices of the companies in the sample, based on the MSE model. Two types of machine learning models were tested with training percentages of 60% and 40%, and 70% and 30%. The study's key finding was the identification of varying prediction capabilities between the two models and for each company individually. The closing stock prices of the companies were predicted for a 33-month period. The study's main recommendation is that interested parties and specialists should adopt this approach. Modern models for testing and prediction, especially those that utilize artificial intelligence techniques

Globalization and the emergence of multinational organizations, as well as the large size of organizations and the diversity of their production, and the scarcity of competent human resources with talent and high technical and technological capabilities have increased the demand for employees from other countries, which has led to the emergence of what are called expatriate employees, whose management is the responsibility of international human resources management. The management of expatriate employees is considered one of the sensitive and complex aspects that require dealing with them with privacy by organizations, because many of them are exposed to failure in their new work tasks in the host country as a result of cultural shocks and the inability to adapt and blend culturally, which leads to the early return of the expatriate employee to his home country, which causes great losses to organizations as a result of not benefiting from their experiences, in addition to travel and transportation costs. Therefore, this article aims to review the literature on the concept of expatriate management, and to indicate the areas that should be focused on to help expatriate employees adapt and integrate with organizations and society, as well as to identify the most important practices that should be followed by multinational organizations and host organizations in order to manage expatriate employees.

The importance of this study stems from the central role of human capital, represented by education and health, in supporting sustainable economic growth, particularly in developing countries such as Malaysia. The study aims to analyze the impact of education and health indicators on economic growth in Malaysia during the period 2000–2023, using the Autoregressive Distributed Lag (ARDL) model based on official annual data. The results reveal a positive long-run relationship between spending on education and health and economic growth, while no significant short-run effects are observed. The study recommends enhancing the efficiency and quality of expenditure on education and health, aligning educational outcomes with labor market needs, and strengthening long-term health policies to ensure the sustainability of human capital’s impact on economic growth.

This study aims to examine the value relevance of accounting information for banks listed on the Iraq Stock Exchange and to analyze how it varies across different measurement models, as well as to compare the findings with evidence from more efficient capital markets. The study employs three measurement models commonly used in the value relevance literature: the price model, the return model, and the earnings–returns model. The results indicate that the value relevance of accounting information differs depending on the measurement model applied, with the price model exhibiting the highest explanatory power, while the return model shows a lower explanatory power despite the earnings variable remaining statistically significant. In addition, the results of the third model reveal that the value relevance of earnings varies according to the direction of stock returns. These findings suggest that the value relevance of accounting information in Iraqi banks exists but is relatively lower than what is typically observed in more efficient financial markets, reflecting the influence of market characteristics such as efficiency, liquidity, and pricing mechanisms. The study concludes that interpreting value relevance results in emerging markets requires careful consideration of the institutional and market context, and it recommends the use of multiple measurement models to enhance the robustness and accuracy of empirical conclusions.

black gold" to adopting renewable energy sources, driven by a reality marked by escalating climate pressures that necessitate a redefinition of the economic role of these nations. The study employs a methodology that combines quantitative data analysis (investment volumes in renewables and emission reduction rates) with qualitative analysis of policies, legislations, and international partnerships, focusing on six main Arab models: Saudi Arabia, the UAE, Qatar, Egypt, Kuwait, and Morocco.
Economically, the study highlights the vulnerability of oil-dependent economies, as falling crude prices expose these countries to shocks in output and fiscal deficits, while countries like the UAE and Morocco demonstrate success in diversifying income sources by enhancing non-oil sectors and investing in clean energy. It also shows that mega-projects such as "Neom" in Saudi Arabia and the "Benban" complex in Egypt contribute to creating thousands of green jobs and driving growth as an alternative to oil.
Environmentally, the study addresses the harms of oil spills and carbon emissions that threaten marine and terrestrial ecosystems, showcasing how major solar energy projects like the Mohammed bin Rashid complex and the Noor Ouarzazate project have contributed to reducing millions of tons of carbon dioxide annually. However, it warns of institutional and social obstacles, such as insufficient necessary financing, dependency on foreign supply for equipment, and land disputes.
The research concludes that achieving a fair and sustainable energy transition requires institutional reforms to enhance governance, the establishment of green sovereign funds to finance renewable projects, and the adoption of Support for decentralized projects in rural areas was also recommended. It suggested involving civil society and the private sector in decision-making, creating an Arab index to measure energy transition performance, and exerting diplomatic pressure on alliances like "OPEC+" to include renewable quotas in their production policies.

This study examines the transmission of monetary policy to real activity in Iraq through a two-block empirical design that links a ConvLSTM forecasting module for key policy instruments with a VAR framework for real outcomes, focusing on the price channel through interest rates, inflation, and the exchange rate and the quantity channel through broad money. Monthly data are compiled from central bank reports and international sources, and stationarity is assessed using Augmented Dickey–Fuller tests to support estimation in levels and reliable dynamic inference. The ConvLSTM is trained for direct multi-step forecasting using 12-month input windows and a 12-month horizon with strict train–validation–test splits, and its accuracy is evaluated using RMSE, MAE, MAPE, and R². The VAR then traces monetary shocks to GDP and investment using impulse responses and forecast error variance decompositions, supported by residual diagnostics and stability checks. Results indicate that expansionary liquidity shocks raise GDP and investment in the short run, while exchange rate depreciation, higher inflation, and policy rate increases dampen real activity, with impulse effects peaking within a few months and fading afterward. The key policy recommendation is to adopt transparent, rule-based liquidity management anchored by credible price-stability commitments, gradual and well-communicated interest-rate adjustments, and macroprudential buffers to limit procyclical risk.

Iraq has continued to experience difficulties in building up its population wellbeing system, especially concerning its normal and disaster-based immunization agendas against children (WHO, 2021). During the last ten years, unstable periods, internal displacement, and limited access to medical resources have also helped to cause sustained variation in vaccination coverage levels (UNICEF, 2020). Health experts and worldwide agencies note that there continue to be considerable disparities in timely and complete provision of childhood immunization with the most concerning areas being in the remote and underserved areas (Ministry of Health Iraq, 2022). Despite the increased rate of access to vaccines against a variety of diseases (especially measles, polio, and diphtheria) due to the national immunization campaigns that have been conducted (GAVI, 2019), high parental acceptability and adherence to follow-through with common vaccines continue to be an issue of concern (Al-Khalisi et al., 2020). Immunization behaviors can be severely affected by a variety of factors such as educational backgrounds of the care givers, cultural beliefs, perceptions of vaccine safety, misinformation, logistical restrictions, and trust in health institutions regarding the care givers (Larson et al., 2016; Dub e et al., 2015). This paper attempts to treat a statistical analysis of major determinants that influence vaccine acceptance and uptake of vaccines in childhood immunization programs in case of health emergencies and regular vaccination campaigns in Iraq. This study also applies powerful and quantitative data analysis tools (such as multivariate regression analysis and factor analysis) to determine whether the demographic, socioeconomic, and attitudinal factors exhibit similar relevance in explanations about caregivers intending to vaccinate their children (Brown et al., 2021). The knowledge that emanates in the course of this analysis is expected to be used to guide evidence-based policies or plans that can be implemented by the public health authorities, NGOs and international partners to improve the rates of vaccination, minimize the number of preventable epidemics, and the overall resilience of Iraq to future public health emergencies (WHO, 2022; UNICEF, 2021).

The main research idea is to identify the impact of successful strategic alignment in senior management on the successful implementation of the ISO 21001:2018 standard. Most organizations today operate in a dynamic and constantly evolving environment, requiring alignment between the variables of both environments to maintain their position in their respective sectors and achieve high-quality services. Therefore, the ISO 21001:2018 training standard is the tool that enables the organization under study to improve the level of services it provides, aligning with the expectations of its beneficiaries. The research problem indicates a deficiency in the organization's understanding of the importance of strategic alignment and its application in fulfilling the requirements of the ISO 21001:2018 training standard. Thus, the research highlights the importance of the recommendations presented as mechanisms for addressing this problem. To translate the research idea into practical results, the descriptive approach was adopted. A questionnaire was designed to collect data, which was distributed to a sample of 131 employees in the Studies, Planning, and Follow-up Department at the Ministry of Higher Education. Several statistical tools available in the SPSS-V23 software were used to process the data. After interpreting and discussing these results, the main and sub-hypotheses of the research were accepted. These hypotheses confirmed the significant role of strategic alignment, through its four dimensions (capabilities, commitment, balance, and control), in meeting the requirements of the ISO 21001:2018 standard for training.

The aims of this study are to measure and analyze the effect of a set of variables (Value added agricultural, foreign direct investment (FDI), gross domestic product (GDP), and agriculture value added per worker, forestry, and fisheries)
or the economic indicators of the green economy on carbon dioxide emissions in Tunisia. The (Eviews13) program was used to analyze the data, and the statistical tests showed the quality of the model based on the value of (R^2), where it was found that 99% of the changes in the dependent variable (carbon dioxide emission) can be explained through changes in the listed independent variables. The most important results were as follows:
Value added agricultural is inversely related to carbon dioxide emissions in the short-term.
The study also revealed an inverse relationship between carbon dioxide emissions and the FDI, GDP, and agriculture value added per worker, in the short-term.
As for the long term, the results were statistically significant as follows:
A direct relationship between carbon dioxide emissions and value added agricultural.
There is a direct relationship between the gross domestic product (GDP) and carbon dioxide emissions in dollar terms.
The more increase in the agriculture value added per worker, forestry, and fisheries the less decrease in carbon dioxide emissions