University of Kirkuk Journal For Administrative and Economic Science

Volume 15, Issue 4, Part 2, Cover

Introduction to Volume 15, Issue 4, Part 2 (in Arabic)

Introduction to Volume 15, Issue 4, Part 2 (in English)

Contents of Volume 15, Issue 4, Part 2

Academic achievement represents the core of the educational process and a key indicator of its actual outcomes, embodying the cognitive outcomes students achieve throughout their educational journey. Based on this importance, the current study aimed to identify the factors influencing the achievement of students at the College of Administration and Economics at the University of Kirkuk.
Study Methodology: The study relied on a descriptive analytical approach, collecting data through a questionnaire consisting of (17) variables, from which a random sample of (254) male and female students for the 2024-2025 academic year was obtained.
Statistical Analysis: Factor analysis (principal component analysis) was used, reducing the variables to five core factors: the quality of the institutional educational environment, active engagement in learning, multidimensional academic pressures, technological-environmental enablement of home learning, and biophysiological barriers to academic performance. Cluster analysis (k-means) was applied to these factors, classifying students into three homogeneous categories (clusters).
Results: Cluster analysis revealed clear variation in the levels of the five factors across student groups. This indicates significant variation in student engagement with the educational environment, differences in the availability of technological capabilities supporting home learning, and variations in the levels of significant health problems. Also, the results confirm the existence of differences in the college environment, which directly impact students' academic achievement patterns.

The study aimed to identify the impact of digital leadership, as represented by its dimensions (digital vision, digital strategy, and digital decision-making), on the dimensions of entrepreneurial orientation, which include (innovation, risk-taking, and proactiveness), in premium hotels in Nineveh Governorate. A hypothetical model was presented to test the main and sub-hypotheses of the study and to answer the questions posed in the research problem.
The study was conducted in premium hotels, and the study population included managers and employees in the hotel organizations in Nineveh Governorate, namely: Ramada Plaza Hotel, Al-Baron Hotel, and Modern Plaza Hotel. A questionnaire was used as a tool for collecting field data, which was distributed manually. All the collected questionnaires (139 in total) were valid for analysis.
The study adopted a quantitative descriptive methodology to analyze the data collected from the field. In this context, the data was collected, analyzed, and the hypotheses were tested using the Statistical Package for the Social Sciences (SPSS). Several statistical methods were used to achieve the study objectives and extract results, including multiple regression analysis.
After conducting the necessary analyses and testing the hypotheses, the study reached a number of findings, the most prominent of which was: there is a statistically significant effect at a significance level (α ≤ 0.05) of digital leadership (in its dimensions: digital vision, digital strategy, and digital decision-making) on the dimensions of entrepreneurial orientation (innovation, risk-taking, and proactiveness) in the surveyed organizations.
Among the key recommendations presented by the study was encouraging the surveyed organizations to focus on the risk-taking dimension by making fundamental changes in their future plans.

Poverty is a phenomenon with serious economic, social, and political dimensions. Therefore, reducing or alleviating poverty is undoubtedly a goal shared by societies, countries, and international organizations working in the field of development. The main objective of this research is to measure and analyze the impact of several variables—domestic investment, unemployment rate, inflation rate, corruption, and political and security instability (specifically the ISIS war)—on the poverty rate in Iraq during the period 2004–2024. This study employs a descriptive and analytical approach to gain a comprehensive understanding of the concept of poverty and its determinants, utilizing econometric methods through time-series data analysis. The findings indicate a strong and significant relationship between poverty and domestic investment, as domestic investment promotes long-term economic growth by increasing productivity and creating new job opportunities. Unemployment has a dual impact on poverty, while high inflation reduces purchasing power. Corruption and the ISIS war have also significantly affected poverty rates. These results highlight the importance of understanding the relationship between these variables. Based on the findings, the research recommends encouraging investments in productive and service sectors, given their vital role in creating sustainable job opportunities and reducing poverty in the long term

This paper aims to study the economic role of agricultural sector, highlighting its contribution to the gross domestic product (GDP), evaluating the size of investments allocated to the agricultural sector and their impact on major crops and reflecting its importance in economic development. Based on the descriptive and analytical approach using percentages, through which the economic role of the agricultural sector during the period (2010-2023) can be studied. The results of this research indicate a decline in the contribution of the agricultural sector to the GDP, excluding oil, from 5.2% in 2010 to 2.8% in 2023.Also,the proportion of investment allocations to the agricultural sector from the total annual investment allocations decreased from 8.6% in 2010 to 1.3% in 2023.The paper shows that the multiplicity of forms of tenure and heterogeneity in agricultural land led to a narrowing of freedom of disposal and the rights of its holders. The paper suggests the need to limit agricultural tenure to two types: A– State-owned lands B– Private property solely owned by individuals and groups, and creating the appropriate institutional atmosphere to stimulate the private sector to expand investment and enter the agricultural and agro-industrial fields, while providing a reassuring investment climate for it.

The current Research aims to identify the level of relationship and influence of psychological empowerment, with its dimensions (meaning, competence, independence, and influence), on organizational Ambidexterity, with its dimensions (searching for new opportunities and optimal exploitation of opportunities), and to demonstrate the relationship between them. The study sample consisted of (42) individuals from the medical staff working at Fallujah Teaching Hospital. The study used a questionnaire to obtain information, consisting of 30 paragraphs. The descriptive analytical approach was used, using the statistical program (SPSS) to arrive at the results. The study reached a set of conclusions, the most important of which is the existence of a statistically significant relationship between psychological empowerment, with its dimensions, and organizational Ambidexterity. The study also recommended the need to pay greater attention to psychological empowerment at Fallujah Teaching Hospital to achieve the desired level of ambition, thus contributing to enhancing organizational Ambidexterity.

Industrial companies today face intense competition both locally and globally as a result of the diversity of customer preferences, the short life cycle of products, and the rapid development of manufacturing systems. Given the crucial importance of cost in ensuring a company’s success and sustainability, it has become necessary to adopt modern cost management methods that align with the contemporary manufacturing environment. With the growing criticism directed at traditional costing systems for their inability to keep pace with the continuous changes in the business environment, there has emerged a pressing need for more advanced approaches that focus on studying the internal and external environments of the product and managing costs throughout its various production stages. These approaches aim to reduce waste, lower costs, and improve the efficiency of resource and time utilization. Accordingly, this research aims to analyze the stages of the product’s life cycle and identify the costs, sources of defects, and losses at each stage in order to enhance the concept of lean production. The research was applied to Khol Industrial Brick Production Company, where the main and sub-activities were identified, and the rates of defects and losses at each stage of the production process were analyzed. The results of the research indicated that the high rate of defects in different stages of the production process leads to significant waste of materials, time, and effort, which negatively affects production efficiency, increases costs, and reduces productivity levels. In light of these findings, the research recommends implementing systematic mechanisms to identify problems at each production stage, measure waste, and estimate its costs. This will contribute to improving production efficiency and continuously reducing waste, thereby achieving the concept of lean production.

This study aims to examine the impact of electronic advertisements via social media networks on the purchasing decisions of youth in (Kalar) city, in the Kurdistan Region of Iraq.
The study sample consists of all youth in (Kalar) city, who use social media networks.
Based on the questionnaire data (number of items = 33), the sample size is determined to be 165 participants.
To prevent the loss of some questionnaires, 200 questionnaires were distributed to the youth, of which 196 were ultimately returned and considered valid for analysis.
This study adopts a descriptive-correlational approach in terms of its methodology. And regarding data collection, it employs a field study design using a questionnaire as the primary instrument.
The data were analyzed using SPSS 30 and SMART PLS 4 software. The results indicated that electronic advertisements — represented by advertisement credibility, design, content, and feedback — have a significant and positive impact on the purchasing decisions of young people in the (Kalar) city via social media networks.

This study focuses on analyzing the challenges facing the adoption of modern technology by small and medium-sized enterprises (SMEs) in rural areas, focusing on the Raparin district in the Kurdistan Region of Iraq as a practical example. The researcher used a descriptive analytical approach, collecting data from 167 participants, including owners, managers, and employees of these enterprises. The data was analyzed using SPSS (version 27).
The study focused on three main dimensions representing the most prominent challenges: financial and economic costs, human resources and technical skills, and the regulatory environment and competitive market. The results showed that the most prominent obstacles were weak technological infrastructure, high costs of technical systems, a shortage of qualified personnel, and weak technological awareness, in addition to the absence of organizational support and strategic planning.
The statistical analysis revealed a statistically significant positive relationship between these challenges and the level of adoption of modern technology. The regulatory environment and competitive market represented the greatest barrier (β = 0.626), followed by financial challenges (β = 0.403), and then human resources (β = 0.271).
The study recommends adopting comprehensive strategies to promote technology adoption, including infrastructure development, financing support, establishing incentive regulatory frameworks, and implementing ongoing training and awareness programs to enhance workforce readiness and ensure sustainable digital development in rural areas.

This study aims to examine the impact of Quality of Work Life (QWL) as an independent variable, represented by its two main dimensions (employee development and work environment), on strategic recovery as a dependent variable within the General Directorate of Education in Salah Al-Din. The research problem arises from the central question: Does QWL contribute to improving strategic recovery among employees in Salah Al-Din Education ، The study adopted a descriptive analytical approach, and its sample consisted of employees in the directorate. A total of 27 questionnaires were distributed, of which 25 were returned and deemed valid for analysis, with a response rate of 92%، Data were analyzed using SPSS through descriptive statistics and linear regression to test the hypotheses، The findings revealed a significant effect of QWL on strategic recovery. Each dimension of QWL independently demonstrated a positive influence on strategic recovery, highlighting the importance of a supportive work environment and effective employee development programs. Results also indicated relatively high mean values for the study variables, reflecting employees’ awareness of the importance of practices that enhance organizational ability to adapt to environmental changes،The study recommends increasing attention to QWL by enhancing training programs, applying the principle of “placing the right person in the right position,” and strengthening managerial credibility in addressing problems to improve strategic recovery capacity.

This study aims to examine the role that the developmental endowment (al-waqf al-tanmuwī) can play in achieving food security in Iraq, particularly in light of the economic and social challenges the country faces due to increasing reliance on imports and the decline of local agricultural production. The research adopts a descriptive and analytical methodology supported by an applied component, using a questionnaire distributed to a sample of specialists and practitioners in the fields of endowment administration, agriculture, and economics, with the sample size exceeding 250 respondents.
The study addresses several key themes, including the management of endowment funds, their investment in developmental projects, endowment-related plans and strategies, as well as the main dimensions of food security—availability, accessibility, utilization, and stability.
The findings indicate that the developmental endowment has a moderate to high positive impact on certain dimensions of food security, particularly in enhancing availability and accessibility, while its influence is weaker with respect to utilization and stability. This reflects a need for further organization and strategic planning in endowment management. The study also shows that activating agricultural endowment investments and strengthening transparency in their administration can help reduce the import gap and promote greater food sustainability.
Accordingly, the study recommends adopting modern endowment models, such as waqf sukuk, and expanding partnerships between endowment institutions, government agencies, and civil society to support national food security.

This study aimed to determine the level of podcast adoption in Kurdish digital media by measuring the objectives and adoption level of media students at Erbil Technical University. The study also sought to identify the sample's demographic characteristics, and reveal their listening habits and preferred patterns.
This is a descriptive study that used a survey methodology. A questionnaire was used as the main tool to collect data from a sample of 114 respondents. The data was statistically analyzed using multiple tests, including Cronbach's alpha coefficient for reliability, Pearson's correlation tests, T-tests, and analysis of variance (ANOVA).
The study's population was media students at the Technical University. The sample was a stratified random sample, primarily based on the demographic characteristics of the population and the sample members. The media dependency theory was employed in this study, given the suitability of its subject matter to the theory's principles and assumptions.
The results showed that the main motivation for using podcasts is to acquire knowledge and develop skills, as 82.5% of the respondents agreed to using them for this purpose. The study also revealed that the majority of the audience are young people (62.3%) with a high level of education. As for platforms, YouTube dominated as the most used platform (50.96%). The results also indicated a statistically significant positive relationship between podcast use and cognitive (learning) and social (relationship building) goals. The study revealed high levels of listener satisfaction, with 82.5% of them recommending podcasts to their friends.

This research addresses a topic of growing importance in contemporary management, namely, the relationship between transformational leadership and organizational creativity. The study aims to explore the extent to which transformational leadership styles influence employee creativity and overcome the challenges associated with constant change in modern work environments.
The researchers adopted a descriptive analytical approach by designing a questionnaire addressed to a sample of 100 employees in four different companies in the province of Sulaymaniyah, covering the telecommunications and industrial sectors (Asiacell, IQ, Mas Factory, and Najmaddin Ready Mix Concrete Company). The number of questionnaires retrieved and suitable for analysis was. The data were analyzed using SPSS software to reveal the nature of the relationship between the dimensions of transformational leadership (ideal influence, inspirational motivation, intellectual stimulation, and individual consideration) and the dimensions of organizational creativity (fluency, originality, sensitivity to problems, flexibility, and risk-taking).
The results revealed a statistically significant relationship between all dimensions of transformational leadership and levels of organizational creativity. It was found that leaders who exert a positive influence on employees through support, motivation, and empowerment contribute significantly to creating a work environment that encourages initiative and innovation. The results also confirmed that employees who work under motivational leadership have higher levels of self-confidence and are more willing to offer unconventional solutions to organizational problems.
The study recommends the development of training programs for organizational leaders that embrace the principles of transformational leadership and the provision of an organizational environment that stimulates creativity by promoting trust, valuing new ideas, and involving employees in decision-making. The study also calls for attention to leadership as a critical factor in improving organizational performance and ensuring continued growth in changing work environments.

This study aimed to analyze and evaluate the impact of applying performance budgeting on the effectiveness of the public budget in governmental units, using the University of Kirkuk as a case study. It sought to measure this impact through four main dimensions of the performance budgeting system: performance measurement system, integration of performance accounting with the budget cycle, reporting and control system, and infrastructure and organizational support. The research adopted the descriptive-analytical approach. Primary data was collected through a specially designed questionnaire distributed to a stratified random sample of (29) employees in the financial and administrative units and departments at the University of Kirkuk. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) to test the research hypotheses using simple linear regression analysis. The reliability of the research instrument was confirmed using Cronbach's Alpha, which showed high reliability. The results of the statistical analysis revealed a statistically significant positive impact of applying performance budgeting on the effectiveness of the public budget through three dimensions: the performance measurement system (explaining 24.2% of the variance), the integration of performance accounting with the budget cycle (explaining 14.1% of the variance), and infrastructure and organizational support (explaining 26.4% of the variance). However, the results did not show a statistically significant impact of the reporting and control system on the effectiveness of the public budget in this sample.

Herein, in this study, we explore the application of regularized regression techniques, incorporating ridge regression with gradient descent, to the prediction of tumor size from hematological variables in breast cancer patients. The standard OLS regression estimation method is problematic in various situations, including multicollinearity, autocorrelation, heteroscedasticity, overfitting, and non-generalizability, particularly in high-dimensional or small sample settings. In consideration of these drawbacks, OLS and ridge regression using gradient descent were compared on a real-world breast cancer dataset according to MSE and R2 in the following. It was found that gradient descent has a better performance than OLS. And it arrived at the result that it got using the statistical packages of the R programming.
These results show the effectiveness of Ridge Regression with gradient descent optimization when dealing with real applied biomedical problems, in this case offering a more viable approach than OLS for predictions of tumor size.

This study presents a comparative evaluation of Bayesian and Classical Repeated Measures Analysis of Covariance (RM ANCOVA) using simulated datasets of varying sample sizes (n = 30, 100, 300). The primary objective is to assess and compare the performance of both methods in terms of model fit, predictive accuracy, and parameter estimation. Simulation data were generated under controlled conditions, incorporating both between-subject and within-subject effects, with a continuous covariate. Classical RM ANCOVA was estimated using frequents approaches, while Bayesian RM ANCOVA was implemented via hierarchical modelling with weakly informative priors, producing full posterior distributions. Performance was evaluated using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute Deviation (MAD). Results indicate that Bayesian RM ANCOVA consistently outperforms the classical approach in small samples, offering lower estimation errors and more stable inference. For moderate and large samples, both approaches yield comparable performance, though Bayesian methods still provide slightly better predictive accuracy and richer uncertainty quantification. The findings highlight the suitability of Bayesian RM ANCOVA for complex longitudinal datasets, particularly when dealing with small sample sizes, unbalanced designs, or violations of classical assumptions. This study contributes to methodological literature by offering a systematic, metrics-based comparison, supporting applied researchers in selecting appropriate statistical tools for repeated measures designs.

This study benchmarks a heterogeneous suite of forecasting models, Multilayer Perceptron (MLP), Simple RNN, LSTM, 1-D CNN, Radial Basis Function network (RBF), Generalized Regression Neural Network (GRNN), and SVR (RBF) on a univariate financial time series, and augments the baseline CNN with metaheuristic hyper-parameter search (Particle Swarm Optimization, PSO). We evaluate models with information criteria (AIC/BIC) under a Gaussian-error approximation in tandem with scale-dependent errors (MSE/RMSE) and produce 12-step-ahead forecasts. The work is motivated by recent evidence that deep architectures can be competitive yet are sensitive to architecture and tuning, and that simpler linear baselines and lightweight neural kernels sometimes rival or surpass complex transformers in long-horizon settings, depending on data regime and evaluation protocol. Our results, therefore, emphasize parsimony versus fit as complementary criteria for model selection and the role of automated hyper-parameter optimization in unlocking CNN performance on short to medium series. The comparative framework, metrics, and forecasting protocol follow the design detailed in the accompanying project document. The study contributes an extensible evaluation scaffold and empirical guidance on when compact kernel methods (GRNN/RBF/SVR) are preferable and when optimized CNNs pay off, thereby informing methodological choices for applied time-series forecasting in data-constrained settings. Recent surveys and competitions are used to position the findings within the broader literature.

This study investigates the impact of taxation on the profitability of food and beverage companies in Erbil city, with the main objective of analyzing how tax policies affect business growth, operational strategies, and competitiveness. The research problem arises from the burden of high tax rates, lack of transparency, and limited incentives, which collectively reduce profit margins and hinder sustainability, especially for small and medium-sized enterprises. The community of the study consisted of food and beverage firms operating in Erbil, from which a sample of 49 companies was selected through random sampling. Data were developed and collected using a structured questionnaire containing 31 items measured on a five-point Likert scale, covering demographic information, tax perceptions, and profitability impacts. The study identified multiple dimensions, including fairness of application, sustainability support, profit margin changes, competitiveness, transparency, and incentive needs. The area of work was confined to Erbil city, the capital of the Kurdistan Region of Iraq. Statistical methodology involved reliability analysis, descriptive statistics, Chi-square tests, and binary logistic regression, using SPSS software. Results showed a significant negative relationship between high taxation and net profits, while complex procedures increased compliance costs. The study recommends simplifying tax systems, enhancing transparency, offering targeted incentives, and reducing VAT on essential goods to improve profitability and support sustainable growth in the sector.

The ethics and practice of the external auditor profession have become important topics that have attracted significant attention from regional and international institutions, companies, and organizations. Auditors who specialize in a particular field are called specialized auditors, as auditors work to improve their expertise in a particular sector by learning more about the unique features of their clients. Therefore, the availability of experience for auditors provides excellent opportunities to conduct high-quality audits for many companies, so that auditors are better equipped to use auditing techniques to detect any fraud and improve the quality of audits now. Research Problem The auditing profession has witnessed significant expansion in recent years due to the financial problems faced by many countries and major global companies. This has led to increased interest in the controls, norms, and principles governing external auditors. International and regional professional institutions have shown great interest in this matter and have issued numerous codes of professional conduct for the auditing profession. Ethics and responsibilities. This study seeks to identify the ethics and responsibilities of the auditing profession and the extent of their contribution to improving the quality of external auditing to achieve its objectives. In order to encompass various aspects of the subject, the researcher will adopt and rely on the descriptive approach. This study conclude that The audit office should allocate a portion of its fees to training and continuing education for the team, as development is always ongoing and must be kept pace with it.

Diabetes is a chronic medical condition that affects millions of people worldwide and poses a serious health risk if not diagnosed early and treated effectively. These datasets consist of ten clinical variables and patient characteristics associated with the diagnosis of diabetes. The data used in this study were collected from patients of Sulaimani Diabetes Hospital for the years 2022 to 2023 and 2024, from which we were able to record information on 192 patients. Each row represents one patient record. The register consists of 10 attributes, of which one is a predictive Y-valued attribute (diabetic, prediabetic, and nondiabetic). Other features are used for the prediction part of the algorithm. Feature selection techniques with two classification algorithms are implemented using Weka programming. The aim of this study is to predict and classify patients with diabetes using two machine learning algorithms: the Multinational Logistic Regression and the Multilayer Perceptron (MLP) model. K-fold cross-validation is used when K = 5, 7, 9, and 10. From the results of this study, we find that the MLR classifier at k=9 achieves the highest accuracy (90.1042%), as in MLP, which has an accuracy of 88.0208% when k=9.

This research paper is an attempt to explore the participant-driven characteristic of strategic optimization of university-based English language centers in the Kurdistan Region of Iraq. The main aim will be to analyze the view of the stakeholders, that is, students, faculty, and administrators about the used international partnership, the desired courses delivery method, and strategies in the functioning of the language centers in the realm of a public university. A survey-based quantitative research design was used to collect data concerning various aspects of perceived effectiveness and levels of satisfaction in several public institutions to find out the entire picture. The results demonstrate that such learning models as hybrid (distributed between online and classroom) learning are preferred highly, as the participants state their versatility and efficiency. Furthermore, the engagement in international affiliations, including associations of well-known international institutions, was seen to contribute greatly to the program credibility, learner motivation and teaching standard. Nonetheless, there are still significant barriers in the form of the technological infrastructure and instructor readiness concerning digital learning. The findings highlight the need to combine the flexible delivery framework and engage international partnerships besides filling the gaps in infrastructural and training baseline to promote sustainable enhancement in English language teaching.
According to the findings, there are limited benefits in involving the international partners, including imperial colleges, which question their contribution to curriculum development, inspiration, and credibility in the eyes of the stakeholders. This study provides a set of actionable recommendations on the part of policy-makers and institutional leaders to restructure the functioning of language centers that should be correlated with the international practice and local contexts.

This research checks the role of environmental costs in improving the quality of financial statements by surveying the opinion of auditors and accounting academics in the Kurdistan region -Iraq. The study is inspired by global changes towards stability and environmental accountability, where the recognition and disclosure of environmental costs has become a necessary component in increasing transparency, loyal representation, perfection and verification of financial reporting. However, in many emerging economies, the disclosure of environmental cost is limited, causing incomplete or potentially misleading information that reduces the decision making of stakeholders.
The study employed a descriptive-analysis method using a structured questionnaire distributed to a sample of academics and practitioners in accounting and audit areas. Conclusions reveal a strong consent on the positive impact of incorporating environmental costs in financial statements, especially in strengthening transparency and stakeholders. Nevertheless, the results also highlight significant obstacles for effective implementation, including weak regulatory structures, limited awareness about environmental accounting and lack of technical expertise.
This research contributes to reducing a significant difference in local literature on environmental accounting and financial reporting quality in the Iraq and Kurdistan region. It provides a scientific foundation and practical recommendations for policy makers, regulators and educational institutions to encourage more transparent and durable accounting practices. The study concludes that integrating environmental costs in financial statements is an important step towards promoting sustainable growth. And strengthening the stakeholder trust.

Exponentially weighted moving average (EWMA) control chart is a statistical method of monitoring the process stability and applies exponentially decreasing weights to prior data observations. Compared with traditional Shewhart control charts, this approach is more sensitive in detecting small shifts in the process mean. When you really need to detect small deviations as soon as possible, the EWMA control chart is ideal. An extended version of the EWMA has been developed to simultaneously monitor multiple linked quality characteristics (Multivariate EWMA (MEWMA) control chart). Such univariate charts might miss the detection of multivariate shifts and this can be referred to MEWMA, since it is based on considering process behavior as a whole by taking into account the relationships among their elements. Further research led to the development of the Bayesian MEWMA control chart, which incorporates historical data or expert views into the monitoring process. By changing the process parameter probability distributions as fresh data grows available, the Bayesian method boosts the flexibility and sensitivity to changes of the chart. In the steel manufacturing sector, When there is a shortage of data or when it is desirable to add prior information, Bayesian inference is very useful. Both preserving high product quality and cutting down on errors are essential for customer satisfaction and operational efficiency. The MEWMA chart and other complementary multivariate control charts are useful for tracking several quality attributes, but they frequently lack the flexibility required for dynamic operations. This study introduces a Bayesian approach to the MEWMA control chart, which leverages Bayesian updating to improve sensitivity to small shifts in quality metrics while accommodating parameter uncertainty.

The purpose of this study is to check the effects of implementing Artificial Intelligence (AI) techniques in large data analysis on cost reduction within the telecom sector in the Kurdistan region of Iraq. Research focuses on four major AI techniques - machine learning, deep learning, natural language processing and expert systems - and their role in increasing operational efficiency, reducing expenses and supporting strategic financial decisions. Big data is emphasized as an analytical environment that enables effective integration of AI applications in cost management processes.
The population of the study included major telecommunications companies in the region, with a sample extracted from three major firms: Korek Telecom (Erbil, Duhok), Asia Cell (Sulaymaniyah), and Sard Fiber (Sulaymaniyah). Primary data was collected through the distribution of 130 questionnaires for finance, accounting and information management professionals. Of these, 122 reactions were received, and 117 were considered valid for analysis. The data was analyzed using statistical methods, including correlation and regression analysis, operational savings, administrative efficiency, labor productivity, future staging maintenance and risk mitigation to test the cost reduction related hypotheses.
Conclusions display a positive and statistically significant relationship between adopting AI techniques within large data environment and cost reduction in identified dimensions. Results indicate that telecom companies take advantage of AI-competent Big Data Analysis, receive more efficiency, low financial waste and customized resource allocation. The study recommends conclusions that the firms have strengthened their potential in AI-managed large data analysis to achieve permanent growth, long-term competition and better financial performance.

Currency depreciation, particularly in emerging markets, poses significant challenges to financial institutions, including Islamic banks. This study investigates the impact of currency depreciation on the financial performance of Islamic banks in Turkey from 2015 to 2023 using a Vector Autoregression (VAR) model. The analysis focuses on key profitability and liquidity ratios, such as Return on Assets (ROA), Return on Equity (ROE), and liquidity indicators. The findings reveal that currency depreciation exerts a negative impact on profitability metrics, with varying effects on liquidity management across the banks. Despite the Sharia-compliant financial structures, which emphasize asset-backed financing and risk-sharing, Islamic banks in Turkey exhibited vulnerability to currency volatility. The research highlights the need for enhanced risk management strategies, particularly in developing Sharia-compliant hedging mechanisms to mitigate currency risks. These results provide important insights for policymakers and financial institutions to improve the resilience of Islamic banks during episodes of economic instability.

We routinely observe longitudinal patterns in medical studies, which track individuals' progress in one or more study variables over time. Most modern modeling techniques assume a parametric dependence of the outcome on time (e.g., linear, quadratic); nonetheless, these dependencies may not be that much dependent on the flow of time. The fixed-effects models are flexible in handling longitudinal data whose pattern is not parametric because the shape of the curve is left to be determined by the data. Although parametric models are one of the most important data analysis tools, they have not been sufficient in some cases.
Therefore, this thesis aims to study methods for estimating nonparametric fixed models for longitudinal data, then compare them to determine which is the best and most efficient, yielding the lowest value for the comparison criteria. These models are then applied to medical data for patients with high blood pressure. To achieve this goal, four methods were employed: Profile Least-Squares, Profile Estimation, Differencing/Transformation Methods, and Marginal Integration. The methods included employing multiple local regression at different degrees and the Gaussian, Cosine, and Epanchnikov kernel functions. Furthermore, a comparison was conducted between the models using five comparison criteria: the mean square error (RMSE), the relative root mean square error (RRSE), the mean relative absolute deviation (MAPE), the mean absolute error (MAE), and the relative absolute error (RAE). The results obtained showed that the Profile estimation method is the best among the methods.

Countries want to increase direct foreign investment for various reasons, such as technology transfer, increasing employment, ensuring growth and development, filling the gap in savings. Direct foreign investment (FDI) has a significant impact on the development of the economy, especially in developing countries. For many years, it was discussed whether financial development affects foreign direct investment in countries. The purpose of this study is to study the relationship between financial development and foreign direct investment in a sample of 39 Asian countries selected for the period 2010-2017, taking into account the importance of foreign direct investment for developing countries. In this connection, the influence of the level of financial development of target countries on foreign direct investment was checked using the generalized method of moments (GMM). As a result of the analysis, it was noted that financial development does not affect direct foreign investments in a certain model. According to the results, economic development plays an important role in FDI, providing stronger investors and expanding access to direct foreign financing through financial development. However, local conditions may limit the degree of realization of FDI advantages.

This study evaluates kernel-specific hyperparameter tuning in Support Vector Regression (SVR) for time series forecasting using a simulated dataset. Four SVR kernels Linear, Sigmoid, Radial Basis Function (RBF), and Polynomial were systematically tested under individually optimized configurations. For each kernel, key hyperparameters including C, epsilon, gamma (used in RBF, Polynomial, and Sigmoid), degree (used only in Polynomial), and coef0 were tuned to enhance predictive accuracy. Performance was assessed using RMSE, MSE, R², AIC, and BIC metrics. Results indicate that the Linear kernel yielded the best overall performance, demonstrating superior generalization and stability. The findings underscore that careful selection and tuning of kernel-specific hyperparameters significantly improve SVR model effectiveness in capturing temporal patterns and reducing forecast error.

The research aims to identify the correlation and impact between blockchain technology (independent variable) and internal audit quality (dependent variable) by surveying the opinions of accountants in a number of industrial companies.To achieve this objective, a questionnaire was adopted and distributed to a random sample of 39 auditors in industrial companies. A total of 34 questionnaires were retrieved, of which 3 were found invalid for analysis, resulting in 31 valid responses. The research relied on the descriptive analytical method to test the research hypotheses and reach the conclusions.
The study reached several key findings, the most prominent of which is that blockchain technology enhances the quality of internal auditing by improving data accuracy and increasing stakeholders’ confidence in financial records, which leads to enhancing internal audit quality and promoting transparency. The research also presented a set of recommendations, the most important of which is the necessity of adopting blockchain technology to help address and overcome work challenges, enabling auditors to effectively deal with the various difficulties and circumstances they may face in performing their duties through the implementation of blockchain related indicators.

In the Kurdistan Region of Iraq, breast cancer is the most common type of cancer, especially among women in the Erbil province. Unfortunately, society views this type of disease with great concern. To investigate the factors that affect the outcomes of breast cancer, in our study, we had to use a robust statistical method, using multifactor analysis of covariance (ANCOVA). Two independent categorical variables, each of which had two levels, which were chemotherapy and age at puberty, were evaluated for their effects on the measures of continuous outcomes, while controlling for the relevant covariate. Our analysis was integrated with a Randomized Complete Block Design (RCBD) to account for the patient's age as a blocking factor, which allows for precise adjustment of baseline variability. In this study, patient data was collected from Nanakali and Rizgari Teaching Hospitals in Erbil city. The level of Immunoglobulin M (IgM), which was obtained from the blood, serves as the primary outcome measure. Comparing ANCOVA with the traditional ANOVA revealed that ANOVA only identified factor B as significant, whereas ANCOVA, by controlling for the covariate, found the significant effects of factor A and the block that ANOVA had missed. Consequently, the study's findings showed that ANCOVA yields more accurate and reliable results by accounting for covariates, which enhances the precision and interpretation of the analyses of treatment outcomes. The study highlights the importance of targeted and evidence-based strategies in the management of breast cancer, also emphasizing the impact of covariates on clinical outcomes.

Iraqi voter trends toward candidates or political parties vary, as these trends can be emotional, behavioral, or cognitive. On the other hand, political promotion is one of the most important tools used to influence voters. Therefore, the current study aims to identify the impact of political promotion on Iraqi voter trends. To achieve the objectives of the research, a purposive sample was selected from the voters of Nineveh Governorate who participated in the (parliamentary and provincial) elections. A total of (230) questionnaire forms were distributed to the research sample, and (200) were retrieved, representing (86.9%). The research reached a set of conclusions, including that there is a significant impact of political promotion on voter trends, and among the most important recommendations is the need to intensify the advertising campaigns of the party or the political candidate in order to achieve greater impact.

This study tried todiscoverArtificial intelligence applications in capturing the talents of newly hired employees at Al-Mamoun Private University and studying their daily behavior within the organizationbyexploring the opinions of employees at Al-Mamoun Private University regarding the applications of artificial intelligence in two areas that we considered the most important in the field of human resources, namely talent management and organizational behavior. In fact, the research focused on understanding the views of these employees concerning whether they are convinced that artificial intelligence, through its various applications, can have positive effects on selecting talented individuals, paying attention to their skills before and after their recruitment and employment, and whether artificial intelligence has a positive impact on their organizational behavior through its different applications.It has been clear from the beginning that employees' responses to the questionnaire were clearly biased towards the importance of the positive role of artificial intelligence in capturing and developing their skills in various work areas. These initial spontaneous responses were confirmed by the analyses we conducted on the data obtained from the survey and data analysis using SPSS. However, what was striking was their outright rejection of the idea that artificial intelligence could have an important and positive role in supporting and effectively managing their organizational behavior, even though the statements included in the questionnaire were designed to measure this. Hence, the researcher emphasized the need to conduct further studies to understand the reasons for the trust in certain aspects of artificial intelligence and the lack thereof in other areas.
It's worth of mention that this study isusing a methodology that includes surveys of staffs, by 39_item questionnaire form which is divided into 19_ item measure of Artificial Intelligence,10-Item measure Talent Management, and finally,10-Item measure the Organizational behavior, furthermore, a random sample of 233 employees from the high and medium management was selected in addition to professors who are working at the studied university. The study’s instrument was distributed in the main location in Baghdad where 150 questionnaires were recovered back and 139 of them were suitable for the analysis of the SPSS software in less than 6 months.

The aim of this study is to examine the role of strategic agility in marketing recovery by analyzing the opinions of managers in private hospitals in the Kurdistan Region/Iraq. The study adopted a descriptive and analytical approach, which is compatible with management studies. Secondary data was collected using readily available sources, including master\'s theses and university dissertations, as well as research published in scientific journals. Primary data was collected using a questionnaire. The study tool consists of a questionnaire consisting of two axes and 40 statements. The research community consists of all managers working in private hospitals in the Kurdistan Region/Iraq, numbering (754) managers distributed across various administrative levels. The researchers distributed (536) questionnaires to the managers, (391) of which were retrieved. The number of valid questionnaires for analysis reached (333), representing the research sample. The research relied on statistical programs such as Excel, SPSS v24, and AMOS v24 to process and analyze the primary data and use it for descriptive tests and tests related to analyzing the study\'s hypotheses. The study found significant correlations and a positive impact between marketing recovery and marketing excellence. The study recommended a set of recommendations, the most important of which are: the need to develop a strategic approach to managing marketing recovery in private hospitals, ensuring the coordination and quality of healthcare services and enhancing the long-term confidence of patients and beneficiaries. This can be achieved by implementing a periodic monitoring and evaluation system that measures the quality of healthcare services provided by the hospital after crises it may face and uncovers shortcomings for prompt remediation.

This research aims to highlight the pivotal role of the capital adequacy ratio in measuring and analyzing the strength and resilience of the financial system in the Iraqi banking sector and enhancing its financial stability in light of the Basel III regulations. It also seeks to determine the nature of the correlation and impact between the capital adequacy ratio and financial stability in commercial banks. The research adopted a descriptive-analytical approach for the theoretical aspect, while the practical aspect relied on studying and analyzing financial data published in the annual reports of five commercial banks listed on the Iraq Stock Exchange during the period (2015-2024). This data was used to calculate the capital adequacy ratio, analyze the results to test the research hypotheses and achieve its objectives, and measure the degree of financial stability using the Z-Score model. Statistical tests were also applied, most notably correlation and regression, along with the application of the Cross-Sectional Effects (SUR) model, using Eviews 12, Excel 2016, and SPSS-23 software to ensure the accuracy of the quantitative analysis. The research concluded that the capital adequacy ratio is one of the most prominent indicators of banks' financial soundness, given its pivotal role in determining the strength of their financial positions and their ability to withstand risks and crises. The results showed that the banks studied adhered to high capital levels exceeding the standards adopted in Basel III and the Central Bank of Iraq, reflecting their financial strength and stability according to the Z-Score model. This demonstrates a direct relationship and positive impact between capital adequacy and financial stability. Therefore, the research recommends that the Central Bank of Iraq direct banks to raise their reserve capital levels in accordance with Basel III. Banks should also adhere to standard criteria and adopt balanced investment policies that achieve a balance between risk and return, while continuously monitoring capital adequacy and financial stability indicators to ensure the stability and sustainable growth of the Iraqi banking sector.