University of Kirkuk Journal For Administrative and Economic Science

This study examines the implementation of strategic planning and management practices in higher education institutions within Sulaimani Province. Using a qualitative approach grounded in literature, theoretical models, and diagrammatic analysis, the paper highlights critical factors that influence successful strategy execution. Drawing on Ricky Griffin’s framework, the study identifies leadership, organizational structure, information systems, and technological advancement as essential elements for effective implementation. The findings indicate that the demand for strategic management in higher education has intensified as institutions face increasing competition, financial constraints, and changing socio-political environments. Strategic planning provides a mechanism to better allocate human and financial resources, improve efficiency, and strengthen institutional legitimacy. The paper emphasizes the role of SWOT analysis as a complementary tool for evaluating internal strengths and weaknesses alongside external opportunities and threats, thereby guiding the achievement of long-term objectives. The study concludes that successful adoption of strategic planning in Sulaimani’s higher education sector requires teamwork, consensus-building, patience, and continuous environmental assessment. These measures are crucial for enhancing performance, accountability, and sustainable development in a region characterized by financial limitations and dynamic socio-political conditions

Most countries strive to avoid dependence on borrowing to finance the general budget deficit, alongside payment of due debts with their interest from another perspective. Iraq can attain this goal by pursuing a sound fiscal policy that reduces wasteful public spending and optimizes and diversifies government revenues in step with the growth of GDP. Such a GDP growth can only be achieved by adopting various measures to reactivate non-oil economic sectors in order to diversified the national economy and attain structural balance in the Iraqi economic framework. In this framework, the methodology of the current study is descriptive-analytical, which is complemented by a quantitative approach, namely the econometric one. It makes use of the Symmetric Quantile test to assess the impact that fiscal discipline indicators have on Iraq's total public debt. Empirical analysis was performed with the use of EViews 13 statistical software.
The results of paper lead to several key conclusions. First: it has been ascertained from the quantile regression results that fiscal discipline has a highly significant impact on public debt levels in Iraq. This conclusion is pertinent to the realities of the Iraqi economy; fiscal discipline acts as a direct instrument to decrease public debt requirements during normal and medium-term debt cycles. The impact of fiscal discipline on public debt levels does not remain constant at a single point; instead, the relationship between fiscal variables and public debt consists of varying signs and magnitude across different debt levels. This has been ascertained from the protocol of the quantile regression results, as the null hypothesis of stability of coefficients was refused by the Symmetric Quantile test. This implies that the impact of public debt created by expenditures, revenues, fiscal balance, and financing varies whether debt levels are low, medium, or high. The model has also explained a good deal of variance at the 0.86 quantile of the distribution; the findings have reflected an acceptable level of statistical significance as the model established an R-squared value of approximately 0.51.

The current study aims to examine the relationship of correlation and impact between dynamic capabilities as an independent variable with its four dimensions (sensing, seizing, reconfiguring resources, and learning) and open innovation as a dependent variable with its two dimensions (inbound open innovation and outbound open innovation), within the context of Asiacell Telecommunications Company in the Kurdistan Region of Iraq as the field of study.
The researcher adopted the questionnaire as the main tool for data collection and relied on the census method by distributing the questionnaire to all senior managers in the investigated company, whose total number was (100) senior managers. A total of (84) valid questionnaires were retrieved and deemed suitable for statistical analysis. The statistical software (SPSS.V.27) was used to analyze the data.
The study reached several conclusions, the most important of which is that dynamic capabilities play a prominent role in achieving open innovation

This study aims to analyze the use of solar energy in residential units in Erbil in 2025, in the context of the challenges related to securing traditional electrical energy supplies. The study aims to measure the impact of applying solar energy on reducing the consumption of traditional electricity and monthly costs for household, as well as exploring the challenges and barriers to adopting this technology. The study adopted a field methodology by distributing questionnaires to a random sample of household in Erbil, in addition to using a logistic regression model to analyze the relationships between variables affecting the adoption and use of solar energy systems. The results showed that the rising monthly costs of traditional energy serve as a strong motivation for household to rely on solar energy, while the challenges related to maintenance costs and the difficulty of scaling hinder the widespread use of these systems. The study also confirmed that providing government support and improving community awareness can significantly contribute to enhancing the use of solar energy, resulting in long-term economic and environmental benefits

The aim of this study is to provide light on how organizational innovation contributes to digital transformation of Asiacell through its dimensions: administrative innovation, technological innovation, and additional innovation. The approach adopted in the study is descriptive-analytical, and a questionnaire utilized as the basic data collection includes 16 items delivered to a sample of 120 employees from the Middle and Senior Administrative Leadership of Company, representing nearly 53% of the total research population for the year 2025, The results reveal a height in the level of administrative innovation, whereas they show a moderation in technological and additional innovations. In addition, the findings demonstrate a moderation in the level of digital transformation in the company, confirming the existence of digital practices which still need further development and expansion. The results of multiple regression analysis state a positive and statistically important impact of the organizational innovation dimensions communally on raising the value of digital transformation, with extra innovation having the most powerful effect likened with the other dimensions. Additionally, the results of the T-test and one-way analysis of variance (ANOVA) do not show any statistically substantial differences in the level of organizational innovation belonging to demographic variables, denoting a homogeneous comprehension among employees concerning the significance of innovation within the company. The validity and reliability tests affirm the exhibition of research instrument for a high level of reliability and internal persistence, in that connection, increasing the precision and credibility of the findings. It is concluded from the study that reinforcing organizational innovation specially by providing extra initiatives and reinforcing the adoption of modern technologies makes up a basic approach to increasing digital transformation and improving institutional performance at Asiacell, thereby raising the value of its efficiency and competitive ability

This study investigates Support Vector Regression (SVR) as a pre-processing filter for Ordinary Least Squares (OLS) in a simple linear regression using simulated data at six sample sizes (n = 50, 100, 200, 400, 700, 1000). An ε-SVR with a radial basis function kernel is first fitted; observations identified as support vectors are retained, and OLS is then re-estimated on this subset. Model quality is evaluated by information criteria. For all n, retention ratios remain consistently high (0.81–0.96) while AIC and BIC consistently decrease post-filtering (ΔAIC from −4.26 at n=50 to −313.29 at n=1000, with almost identical ΔBIC). This implies a meaningful increase in penalized likelihoods without a change to OLS parameterization. Thus, these results support SVR as a reliable denoising filter for enhancing a linearized signal in future estimation, creating a low-cost and easily repeatable avenue to improve classical regression results when faced with noisy or structurally mismatched observations

This study examines the effectiveness of a parsimonious state-space framework for modeling and forecasting the weekly Bitcoin opening price amid strong trends, regime shifts, and time-varying volatility. A Dynamic Linear Trend (DLT) model is employed, in which Bitcoin prices are decomposed into latent level and slope components that evolve stochastically over time, allowing the model to adapt flexibly to changing market conditions. Stationarity is assessed using first differencing and the Augmented Dickey–Fuller test, supporting an integration order of one and motivating the chosen specification. Model estimation and inference are carried out using the Kalman filter, enabling recursive state updating and probabilistic forecasting. Competing model dimensions are evaluated using the Akaike and Bayesian Information Criteria across training and testing samples. The results indicate that the simplest specification (k = 3) consistently minimizes both criteria, suggesting that additional parameters do not provide sufficient improvements in model fit. Short-horizon forecasts point to a broadly flat to mildly declining price trajectory over a 12-week horizon, while widening predictive intervals reflect increasing uncertainty. Overall, the findings demonstrate that Dynamic Linear Models offer an interpretable and statistically coherent approach to short-term Bitcoin price forecasting, delivering well-calibrated uncertainty estimates while avoiding over-parameterization

The research aims to study and analyze the impact of artificial intelligence technologies on accounting reporting, by surveying the opinions of a sample of academics and professionals in the city of Erbil. This research comes in response to the rapid developments in artificial intelligence technologies, which are beginning to have a clear impact on various areas of business, including accounting and accounting reporting systems. The research dealt with the relationship between the two variables by organizing a questionnaire addressed to a sample of academics and professionals in the field of accounting. The data were analyzed using appropriate statistical tools such as arithmetic averages, standard deviations, and some inferential tests (T-Test) and (ANOVA). The research reached a set of results, most notably: there is a growing awareness among the sample members of the importance of artificial intelligence in improving the quality and reliability of accounting reporting, with a disparity in the level of practical application of its technologies among companies, and the results showed that there are multiple challenges facing the process of integrating artificial intelligence in accounting, including a lack of qualified cadres, and inadequacies in technological infrastructure. In conclusion, the researchers recommend the need to enhance professional and academic awareness of artificial intelligence technologies, and develop educational curricula and accounting practices in line with the requirements of the digital age, to ensure the provision of accurate and transparent financial reports that support decision-making

Accurate forecasting of silver prices is essential for investors, policymakers, and industrial stakeholders due to the metal’s dual role as both an investment asset and an industrial input. Silver price dynamics are characterized by strong nonlinearity, volatility, and regime changes, which limit the effectiveness of traditional linear time-series models. This study proposes a hybrid machine-learning framework for short-term silver price forecasting based on Support Vector Regression (SVR) and two metaheuristic optimization techniques: Genetic Algorithm (GA) and Bat Algorithm (BAT). Daily silver prices (XAG/USD) from 1 February 2025 to 1 February 2026 are used, and a lag-based supervised learning structure is adopted. Model performance is evaluated using a realistic one-month backtesting design and multiple criteria, including mean squared error (MSE), root mean squared error (RMSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Empirical results demonstrate that both optimized models significantly outperform the baseline SVR, with GA-SVR achieving the highest predictive accuracy and the best balance between goodness-of-fit and model complexity. Forecast uncertainty is assessed through bootstrap-based 95% confidence intervals, while residual diagnostics using the Augmented Dickey–Fuller test confirm the adequacy of the selected model. The findings highlight the effectiveness of hybrid SVR–metaheuristic approaches for modeling nonlinear silver price dynamics and provide a reliable, uncertainty-aware forecasting framework for short-term decision-making

Job burnout is one of the most important problems suffered by workers in various types of business organizations, which may affect their mental and physical health in the workplace. Job burnout significantly affects the performance of organizations and the well-being of individuals. Based on the theory of compatibility between the individual and the work environment through the use of the methods and mechanisms of teamwork, this research conducts a quantitative study of the psychological mechanisms of compatibility between agile work teams and their role in linking and influencing job burnout. To achieve the research objective, a survey was conducted on a representative random sample of 80 individuals working in the Mosul Municipality Directorate, through the distribution of a questionnaire prepared for this purpose. The statistical analysis software Amos 24 was used, and the research reached several conclusions, most importantly that the two research variables (lean work teams and job burnout) are present in the Mosul Municipality Directorate from the perspective of a sample of employees. The proactive dimension ranked first in terms of relative importance. Furthermore, there is a strong negative correlation between lean work teams and job burnout. The research also showed an impact of lean work teams on job burnout, with the demographic factor (gender) having a higher impact on job burnout among females than males. The research presented a set of recommendations, including the need for the management of the studied organization to pay attention to the mechanisms of self-directed work teams (lean work teams) through guidance and awareness of the importance of lean work teams and implementing changes in work mechanisms within these teams. It also emphasized the importance of providing opportunities for team members to discuss work ideas, team goals, and the objectives of the team's work with each other, and facilitating discussions about the similarities and differences in the perceptions of other groups regarding work teams

This study aims to reveal the role of wearable smart products in enhancing the consumer experience. This was achieved through a survey of employees in smart device and mobile phone sales and service centers, as they are key players in marketing these products and serving their users, in addition to being familiar with user experiences. The study adopted a descriptive-analytical approach, as it aligns with the nature of its objectives and variables. The study population consisted of employees in several smart device sales and service centers, from which a random sample of 150 respondents was selected.
To collect data, a questionnaire was designed based on relevant literature and previous studies. It included a set of items measuring the dimensions of wearable smart products and the dimensions of the consumer experience. The validity and reliability of the instrument were verified using appropriate statistical methods. The study employed several descriptive and inferential statistical methods, utilizing specialized statistical software to analyze the data.
The study results showed a significant and positive impact of smart wearable products on improving the consumer experience by enhancing satisfaction, ease of use, and service quality. These products also contribute to increased consumer loyalty and brand trust. The results further highlighted the crucial role of sales and service center staff in guiding consumers toward optimal product use, thus positively impacting their overall experience.
The study recommended that companies and specialized centers prioritize developing their employees' technical and marketing skills, improving after-sales services, providing ongoing technical support to users, and keeping pace with technological advancements in wearable products. This will contribute to enhancing the consumer experience and achieving a sustainable competitive advantage

This research addresses the estimation of non-parametric extropy for length-biased data using an Expectation-Maximization (EM) iterative algorithm. Extropy serves as a complementary measure to entropy in measuring uncertainty, and its estimation faces significant challenges when data is biased. Therefore, the study aimed to develop an iterative framework (EM-KDE) that combines the Expectation-Maximization algorithm with kernel density estimation to enhance the accuracy of conclusions. The research relied on simulation results to analyze the impact of different methods used in estimating extropy. The findings revealed that the true extropy estimate was -0.1250, while the uncorrected estimate yielded a value of -0.0897, indicating a bias of 0.0354. In contrast, the corrected estimates, including the adjusted kernel density estimation (W-KDE) and the EM-KDE algorithm, both provided a value of -0.1046, reflecting a notable improvement and a reduction in deviation from the true value by 42.3%. Thus, the study recommends adopting corrected methods when analyzing biased data and conducting further research to explore new estimation techniques, in addition to developing analytical tools that facilitate the application of these methods in future research

Multicollinearity is a familiar problem in linear regression analysis; this phenomena arise when the relationships among explanatory variables exist. Ordinary least squares (OLS) is used to estimate parameters in regression analysis when it is assumed that there is no correlation between explanatory variables. When the assumption of multicollinearity is not valid, one should attempt to use different techniques to deal with the problem, because it affects the accuracy of the regression coefficient. Ridge regression (RR) is a special case of OLS that allows Biase to estimate parameters more precisely. Partial least squares regression (PLSR) and Principal component analysis (PCA) are both techniques that build new predictor variables known as components as linear combinations of the original predictor variables. These components are built in different ways. PLSR builds a component to explain the observed variability in predictor variables and involves a response variable; also, PCA builds a component like PLSR without a response variable, it just transforms the predictors into uncorrelated components, and principal component regression (PCR) applies to the uncorrelated components to regress the outcome response variable on those components. The performance of RR, PLSR, and PCR was compared to detect the effective technique to overcome the collinearity problem in a real data set

This study examines the influence of customer-centric marketing strategies on consumer loyalty in the context of businesses in Erbil, Iraq. Customer-centric marketing is a popular idea in today's markets, but many businesses find it hard to put it into practice. The study employed a mixed-methods research design to gather data from 250 respondents via structured questionnaires, supplemented by interviews and document analysis. Descriptive findings indicate that essential customer-centric practices—such as personalization, responsiveness to feedback, comprehension of customer pain points, and proficient utilization of customer data—are inadequately executed by the majority of organizations. This poor performance is linked to low levels of customer loyalty, which is shown by weak repeat buying, a lack of emotional connection, low trust, and little brand advocacy.Logistic regression analysis shows that the overall model is statistically significant, but only certain practices—like addressing customer pain points and adapting to customer expectations—are good at predicting higher loyalty scores. The study finds that in order to improve customer loyalty in competitive markets like Erbil, businesses need to use more customer-focused strategies and make decisions based on data. They also need to keep building relationships with customers. There are useful suggestions that can help businesses plan better marketing campaigns that focus on their customers

The research aimed to measure the correlation and influence relationship between the independent variable, flexible leadership, with its dimensions represented by (work, human relations) and organizational inertia as the dependent variable embodied in the following three dimensions: (inertia of insight, inertia of action, and psychological inertia) in the Salah al-Din Education Directorate. The research was based on the descriptive and analytical approach in dealing with the theoretical and conceptual aspects, analyzing data and interpreting its results. The field of research was limited to the Salah al-Din Education Directorate, and the research community included all individuals working at various administrative and technical levels in the department. The research sample was chosen randomly from among the individuals working in it. The questionnaire was used for the purpose of obtaining primary data from the individuals surveyed, as their number reached (230) individuals. The research relied on a number of statistical methods to process and analyze data with the aim of investigating respondents’ opinions and attitudes regarding the questionnaire items, and among these methods are (honesty coefficient, Cronbach’s alpha coefficient, arithmetic mean, standard deviation, percentages). Accordingly, the research reached several results, the most important of which is: Flexible leadership is inversely related to organizational rigidity. Which indicates that the field under study has the ability to eliminate flexible leadership and limit the manifestations of organizational stagnation

This research is aimed to analyze the role of Management Information Systems in increasing the effectiveness of rapid response to internal crises at Presidency of Middle Technical University through the analysis of the relationship and impact of the study variables in an organizational environment dependent upon information flow and the rapid decision making. The approach used in the research was descriptive analytical and the main instrument used for collecting data was a questionnaire distributed to 140 administrative leaders, employees and technicians as sample of the total population. The study centered on three components of Management Information Systems (MIS) which are information quality, system quality and technical support and decision support. Rapid response effectiveness comprised of three factors: sensing and information transfer speed; decision making speed; and implementation and treatment speed. The results showed that the level of Management Information Systems and the response to internal crises was high, with a positive correlation between the two, and that the degree of Management Information Systems had a direct effect on the effectiveness of the response in internal crises. The findings also indicated that technical support and decision support were the most influential dimension to enhance the response to the crisis. The results of the research showed that the development of Management Information Systems has a positive impact on the administrative performance improvement and strengthening of the ability of the institution to face internal crises effectively.

The aim of this study is to identify the nature of use, direct impact, and correlation between digital marketing elements and customer behavior, and to determine if there are any apparent differences. The importance of the study stems from the observation that there are concepts from various companies worldwide, and the attempt to invest in and adapt them to the Iraqi environment. Based on what is presented, the problem of drawing the main question is: (How can the content of digital marketing be used to promote customer citizenship behavior, and how can the relationship between them be activated through the mediating role of promotional innovation?), The data study was covered using a continuous questionnaire model and a main data monitoring tool, which was distributed to a number of tourists, which amounted to (185) tourists. The descriptive method was used to try to answer the study questions and test its hypotheses. The difference and direct impact were measured using statistical programs (SPSS 23, jasp). The study concluded that there is a significant relationship between new digital marketing changes and changes in customer behavior. In addition, there is an impact of digital marketing changes on customer behavior, while direct marketing changes do not affect customers, with the contribution of promotion acting as a mediating variable

The research study will explore the influence of elements of the marketing mix on buying decisions to assess the influence of product innovation and price perception and channel performance and promotional effectiveness on purchase intent and brand decision making. In this research, data collection is done through a structured questionnaire and descriptive and inferential statistical analysis including multiple regression and subgroup testing and mediation analysis. They discovered that marketing-mix variables were responsible for a significant portion of the change in buyer intent with an explanation rate of R2 = 0.674. The findings show that product innovation and distribution, as well as promotion effectiveness, all had positive effects on the intent to purchase. They found negative price perceptions decrease consumer purchasing intent because price perception has a strong negative effect on purchase intentions. The marketing mix has positive effects for all age groups. Although the effects of the marketing mix are similar, the size of the effects varies between the younger and older consumers. The mediation testing results suggest that the product innovation is a partial mediator since the indirect effect is 0.134 and the direct effect is 0.423 with a total effect of 0.557. Overall, the effect passes through mediation corresponding to about 24.1% of the effect path. These studies suggest that companies must combine their 4P decisions with establishing specific plans to target different markets and consumers to further increase brand performance and increase purchasing behavior

This research aims to understand the role of production technology engineering in achieving organizational excellence, as production technology engineering is a fundamental pillar in developing organizational performance and achieving excellence. production technology engineering aims to improve production processes, increase efficiency, and reduce costs by applying advanced methods and processes. The sample consisted of managers from an electrical manufacturing company. The importance of the research is highlighted through the results obtained by interpreting and analyzing the responses of the 60 respondents. A questionnaire was used, prepared according to a five-point Likert scale. Statistical methods, including standard deviation and mean, were employed, along with analytical models such as linear regression and correlation coefficient. The SPSS software was used for data analysis. The research concluded that production technology engineering contributes to strengthening relationships for achieving organizational excellence. The most important recommendation is to encourage the company in the study sample to develop its production processes by using appropriate technology, improving the flow of materials and information, reducing waste, and achieving high product quality

This study examines the extent to which accounting information systems in Iraqi commercial banks meet the sustainability and climate disclosure requirements of IFRS S1 and IFRS S2 issued by the International Sustainability Standards Board (ISSB). Using a descriptive-analytical approach based on content analysis of the annual reports of a sample of ten banks listed on the Iraqi stock exchange during the period 2022–2024, and relying on a robust checklist to measure compliance with the standards and the quality of accounting disclosure, the study sought to test the relationship between sustainability disclosure requirements and the readiness of accounting information system outputs. The results indicated that the banks demonstrated a significant level of compliance with the general disclosure requirements related to governance, strategy, and risk management under IFRS S1, while compliance with climate disclosure requirements under IFRS S2 was very limited and often confined to general descriptive statements without measurable quantitative indicators. The results also revealed a weak statistical relationship between the level of compliance with standards and the quality of accounting disclosure, reflecting that current compliance is more formal than actual implementation reflected in system outputs. Based on these findings, the study recommends developing the technical infrastructure of accounting information systems, expanding non-financial databases, and enhancing human resources capabilities. This will enable banks to gradually transition towards integrated and sustainable financial disclosure, particularly given the increasing importance of climate disclosure at both the local and international levels

This research aims to analyze the impact of digitalization variables on economic growth in Iraq during the period 2004-2024. It examines the effect of several digitalization indicators (e-services rate, value added in the ICT sector, human capital, government digital governance, number of internet subscribers, number of telephone users, telecommunications infrastructure, and number of bank branches) on economic growth. The research employs an inductive-analytical approach. The findings indicate that the e-services rate and the number of bank branches have a significant positive impact on economic growth in both the short and long term. However, the government digital governance indicator has a significant negative impact. The remaining variables, such as value added in the ICT sector and human capital, have a significant negative impact.The number of internet subscribers, the number of telephone users, and the telecommunications infrastructure did not show a significant impact on economic growth in the short or long term. The research also demonstrated that digitalization is not merely a technology, but a strategic choice that can contribute to economic diversification and reduce dependence on oil. This research offers an analytical perspective on the role of digitalization in promoting economic development in Iraq, contributing to the formulation of more effective digital and strategic policies

Given the Brazilian economy's heavy reliance on oil over the past two decades, despite diversifying his sources of income, particularly with increased exploration and production activities in its territorial waters, it is essential to examine how oil prices affect public spending in Brazil. This research aims to analyze and measure the impact of oil prices on Brazilian public spending during the period 2004–2023, using an Autoregressive Distributed Limiting (ARDL) model and its pre- and post-estimate econometric tests. Public spending was adopted as the dependent variable and oil prices as the independent variable, with two control variables (exchange rate and GDP) included in the econometric model only, without theoretical or descriptive analysis, to enhance the model's explanatory power. The econometric analysis results showed that oil prices had a significant positive impact (at a significance level of 1%) on Brazilian public spending in both the short and long term. In the short term, the impact was 0.998%, attributed to the rapid response of public spending to improved oil revenues and the overall fiscal position. In the long term, the impact remained positive, albeit at a lower level of 0.076%. This is attributed to the diversified Brazilian economy's ability to absorb fluctuations in oil prices, as well as its adoption of a more prudent and stable long-term fiscal policy. These findings suggest that oil prices are a contributing factor, but not the dominant one, in determining the trajectory of public spending in Brazil

This study aims to analyse the role of proactive marketing as an independent variable, through its dimensions of risk-taking, innovative ability, market sensing, and flexibility, in achieving marketing excellence as a dependent variable, represented by maintaining required quality, customer retention, core capabilities, and continuous improvement, within private banks operating in the Kurdistan Region of Iraq. The study is based on the perspectives of bank managers, who are responsible for shaping marketing orientations and making strategic decisions in a banking environment characterized by intense competition and rapid market changes. The research adopted a descriptive analytical approach. Data were collected using a questionnaire. A comprehensive census method was employed targeting managers of the investigated banks. A total of (451) questionnaires were distributed, of which (411) were returned, yielding a response rate of (91.1%). After screening, (400) questionnaires were found valid for statistical analysis, representing (88.7%) of the distributed questionnaires and (97.3%) of the returned ones, forming the final study sample. Data were analysed using SPSS V24 through various descriptive and inferential statistical techniques. The findings revealed a statistically significant correlation between proactive marketing and marketing excellence at the overall level, as well as varying strengths of correlation between their dimensions at the partial level. The results also indicated a significant effect of proactive marketing on achieving marketing excellence. The study concluded with several findings and recommendations emphasizing the importance of adopting proactive marketing practices as an effective strategic approach to enhance marketing excellence in a dynamic and rapidly changing banking environment

This study aims to analyze the role of the green economy in supporting sustainable economic growth in Iraq and Egypt during the period (2015–2024), using indicators of renewable energy, carbon dioxide emissions, and gross domestic product. The study adopts a descriptive–analytical and comparative approach to examine trends in the transition toward the green economy and their economic and environmental impacts.
The results indicate that Iraq faces significant challenges in adopting green economy policies due to heavy reliance on oil revenues and limited green investments, which has constrained sustainable growth and emissions reduction. In contrast, Egypt has achieved noticeable progress in green economy indicators, particularly since 2017, through expanding renewable energy projects and improving energy efficiency, which positively contributed to economic growth and employment.
The study concludes that the green economy represents an effective tool for achieving sustainable development and recommends integrating environmental considerations into national economic policies, especially in Iraq, while benefiting from Egypt’s experience in green economic transformation

Pension and social security systems are obviously fundamental to maintaining social and economic stability, especially in environments where the labour market is expanding further in the private sector and international institutions. In the Iraqi Kurdistan Region, there is an increasing need to investigate the role of the pension and security system in promoting force stability, commitment and participation, given the unequal levels of protection between the public and private sectors.
The overall objective of this study is to analyse the impact of social security and pension fund mechanisms by testing the mechanisms on four main dimensions: job security, transparency, life affordability and perceived value on labour force participation in private sector institutions.
Data were collected through an electronic questionnaire distributed to a stratified random sample of 348 eligible forms consisting of employees of private universities, international companies and local and international NGOs. Data were analysed by using SPSS and AMOS software and based on natural folds of data, confirmatory factor analysis (CFA), and structural equation modelling (SEM).
Based on the results of the study, it was found that the explanatory power of the model is high and the pension fund and social security mechanisms have a strong, statistically significant and meaningful positive effect on overall labour force participation. The results also revealed that the dimension of transparency was the strongest influence, followed by perceived value, job security, and while the fourth dimension, the life affordability, had a relatively lesser impact. And the findings tell us that improving the efficiency, transparency and sustainability of fund mechanisms significantly plays a role and impact in enhancing institutional trust and employee engagement.
The study concludes that there is a need to develop clear regulatory frameworks and effective retirement mechanisms in the private and international sectors, in order to support job stability and social sustainability in the Kurdistan Region of Iraq

This study aims to explore the role that relationship marketing strategy, with its four dimensions (trust, commitment, communication, and satisfaction), can play in achieving sustainable marketing with its three dimensions (social, economic, and environmental) in private universities and colleges in Kirkuk Governorate. This is because Kirkuk Governorate is considered( a miniature Iraq) due to its diverse ethnicities, religions, sects, and educational systems. The study employs a descriptive-analytical approach and utilizes a questionnaire as the data collection tool. Three hundred (300) printed questionnaires were distributed to the sample, and (264) were returned. All (264) questionnaires were deemed valid for statistical analysis, representing ( 88% ) which is acceptable for scientific research purposes. Several statistical methods were used to analyze the data, including (Cronbach's alpha for reliability, factor analysis, simple correlation, and structural equation modeling using program (AMOS-26 and SPSS- 26),and the results showed a correlation and impact of relationship marketing strategy, with its four dimensions on achieving sustainable marketing with its three dimensions. Based on the results of the study, a number of recommendations were presented to the colleges and universities studied in Kirkuk Governorate specifically to develop future studies in this field (the field of private education)

Strategic audit plays a pivotal role in enhancing transparency and accountability in government institutions, especially in countries facing major financial and administrative challenges such as Iraq. The strategic audit enhances transparency in government institutions by analyzing government performance using measurable indicators, not just financial, but also environmental and social. This study seeks to measure the level of environmental and social transparency in the Iraqi government sector using approved international indicators and determine the impact of strategic auditing on the level of transparency in the government sector, The research helps decision makers in government institutions understand the areas in which auditing is needed and link them to quantitative indicators of transparency, The research also contributes to raising the level of transparency and accountability, which enhances public confidence and reduces the chances of financial and administrative corruption, The research found that regulatory bodies in government institutions have a positive attitude towards strategic audit practices, as they believe that they contribute to improving strategic planning and evaluation, risk management, enhancing governance and compliance, in addition to raising the level of transparency and financial disclosure and increasing the reliability of published data. External factors such as government policies, political stability, and community participation play an influential role in the level of transparency, which reduces the clarity of the impact of the strategic audit

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This research involves investigating the global role of Employed (System Utilization) competence, involvement, and the organization climate as a means of optimizing the Enterprise Resource Planning (ERP) systems for financial reporting and organizational performance. Unlike previous research on the technical aspects, it emphasizes the human factor as a key to gaining benefits from technological investments as financial success. Using quantitative descriptive design, 225 professionals with the best organizations in Kurdistan Region of Iraq were surveyed. Results showed that there was a strong correlation between employee proficiency, organizational support and improved accuracy, transparency and timeliness in financial reporting. The study suggests moving beyond symbolic ERP adoption through human capabilities development through training and participatory culture, through minimizing technostress and through facilitation of system dependence to provide financial integrity and competitive advantage in the digital economy

This research aims to study the impact of sovereign green bond issuance on government borrowing costs in a group of developing countries during the period (2010–2024). The study adopted a panel data approach using the dynamic generalized least squares model (GMM) to address the issues of auto-dependency and inverse causality between financial and economic variables. The experimental results show that issuing green bonds significantly reduces government borrowing costs, confirming the existence of a "green premium" that reflects investors' preference for sustainable instruments. Trade liberalization is negatively correlated with borrowing costs, while higher public debt leads to a temporary increase in financing costs before its negative effects on fiscal sustainability become apparent. Economic growth has a non-linear relationship with borrowing costs, meaning it does not necessarily translate into improved financing conditions. The findings suggest that adopting green finance offers developing governments an opportunity to enhance their environmental credibility and improve international investor confidence, thereby reducing public debt costs and supporting long-term fiscal sustainability

This study evaluates the effectiveness of monetary policy in Lebanon during the period 1997–2025 by applying the "Extended Taylor Rule" framework. The research aims to analyze the response of nominal interest rates to macroeconomic variables, specifically the inflation and output gaps, while emphasizing the pivotal role of foreign reserves in a small open economy characterized by a long-standing currency peg. The methodology employs an econometric analysis of annual data, utilizing the Ordinary Least Squares (OLS) method with Newey–West (HAC) standard errors to address potential autocorrelation and heteroskedasticity. Empirical results demonstrate that both the inflation gap and the output gap were statistically insignificant in determining interest rates, suggesting that Lebanese monetary policy did not follow traditional rules focused on internal stability. Conversely, foreign reserves exhibited high statistical significance at the 1% level with a strong negative coefficient (-8.364), confirming that the preservation of reserves and the defense of the exchange rate were the primary drivers of monetary policy. The findings further indicate that the 2019 financial crisis forced a fundamental shift toward reactive crisis management, leading to stagflation as the previous economic model collapsed. The study concludes that Lebanon's monetary policy has been constrained by external stability requirements at the expense of domestic growth and recommends an overhaul of the monetary framework to restore credibility and support sustainable recovery

Objective: Contemporary universities are increasingly aware of the gap between traditional leadership styles and the accelerating demands of digital innovation for business sustainability. However, a comprehensive framework demonstrating the importance of "integrated leadership" (which combines transformational and digital attributes) in fostering sustainable digital transformation has not yet been proposed. This study aims to provide a comprehensive vision by proposing a structural model highlighting the importance of adopting hybrid leadership styles and their role in the successful implementation of digitalization in Iraqi universities. The model was developed based on advanced frameworks for digital management and transformational leadership.
Design/Methodology/Approach: To collect data, an electronic questionnaire was distributed to 429 leaders from the teaching and administrative staff of selected Iraqi universities. Second-Order Structural Equation Modeling (SEM) was used in AMOS (version 26) to analyze the data and test complex hypotheses. Results: The results revealed the significant importance of the study model, demonstrating a strong and statistically significant positive impact of integrated leadership styles on sustainable digital transformation, with an impact factor of 0.672. The results also showed that the leadership influence is robust and stable, as no significant moderating role for technological disruption was found in this relationship (P = 0.143).
Research Limitations/Implications: We can conclude that adopting an integrated leadership style in academic institutions is a cornerstone for improving employee performance and ensuring the continuity of technological change. This model provides university leaders and decision-makers with an opportunity to effectively manage complex digital transformations by balancing inspirational motivation with technical expertise. Despite limitations related to sample size and sector type, we focused on the interaction between leadership and technological disruption, which opens avenues for future research in other technologies such as artificial intelligence.
Originality/Value: This study is one of the first in Iraq to develop a composite structural model that explains how transformational and digital features can be integrated to create an innovative academic environment resilient to technological disruptions. It also fills a crucial gap in the literature regarding the resilience of leadership influence in volatile digital environments

This study aims to analyze the role of environmental auditing in reducing greenwashing practices in industrial companies by examining the relationship between the five dimensions of environmental auditing—environmental standards compliance, efficiency of environmental processes and procedures, transparency of environmental reporting, corrective follow-up and continuous improvement, and top management support—and greenwashing practices in their various dimensions. The study adopted the descriptive-analytical approach, and data were collected through a questionnaire consisting of 39 items designed on a five-point Likert scale. The questionnaire was administered to a purposive sample, yielding 65 valid responses from industrial companies.
The descriptive results indicated that environmental auditing was practiced at a relatively high level, with a mean score of 3.86 and a relative importance of 77.2%, whereas greenwashing practices were found at a moderate level, with a mean score of 3.51 and a relative importance of 70.2%. Correlation analysis revealed a strong and statistically significant inverse relationship between environmental auditing and greenwashing (r = -0.62, p < 0.01). In addition, simple linear regression analysis showed that environmental auditing explains 38% of the variance in greenwashing practices (Beta = -0.62, F = 55.5, Sig = 0.000).This study contributes to the accounting literature on environmental auditing within the Iraqi industrial context and offers practical recommendations for policymakers and managers to strengthen environmental transparency and reduce deceptive practices associated with greenwashing

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This research aims to determine the role of digital transformation strategy in building agile organizational capabilities, specifically within the telecommunications company Asiacell. To achieve this, the dimensions of digital transformation strategy (leadership, infrastructure, resources, and cybersecurity) were adopted, along with the agile organizational capabilities (responsiveness, responsiveness, flexibility, and capability). Asiacell was selected as the case study through a questionnaire distributed to 69 respondents from various departments, divisions, and units within the company. The normality test was used for the data, and the statistical software package SPSS (version 25) was employed to test the hypotheses. One of the key findings is that digital transformation strategy effectively contributes to building agile organizational capabilities within the company. The research concludes with several recommendations, most notably the necessity of adopting a comprehensive digital transformation strategy at the Asiacell level and directly linking it to the objectives of improving service quality and accelerating response to subscriber needs

This paper sought to examine how servant leadership can help to decrease job burnout through organizational climate as a mediator with the help of a field study on Kirkuk University. The descriptive analytical approach was utilized in the research because it is appropriate to the variables under study. The data collection instrument was a questionnaire which has been created to test the dimensions of servant leadership, organizational climate, and job burnout. The population of the study was Kirkuk University, where all the administrative heads of the different departments in the university were involved. The sample comprised (280) administrative leadership at the main and sub-level of leadership. The statistics were performed on the basis of SPSS and AMOS. The findings of the study indicated that servant leadership has a major role to play in alleviating employee burnout. It also showed that organizational climate that is positive is a mediator in nurturing this relationship in enhancing the health of organizations in learning institutions. The research suggested the encouragement to use servant leadership styles within universities, where they would help remove work-related stresses and provide a balance between work obligations and organizational needs of employees

This study investigates the prioritization of key accounting determinants, specifically financial capital and intellectual capital, and assesses their impact—alongside the banking sector index as an external environmental factor—on the financial performance of commercial banks. A descriptive-analytical approach was employed to analyse financial data and reports from a sample of five commercial banks listed on the Iraq Stock Exchange between 2020 and 2023, utilizing SPSS v.26. The findings indicate that accounting determinants exert a more significant influence on financial performance than the external environmental factor represented by the banking sector index. Among the indicators analysed, human capital efficiency, ownership concentration, and management efficiency were identified as having the highest impact on financial performance in order of importance. Conversely, innovation capital efficiency, competitive advantage, and communication capital efficiency were deemed less impactful. Based on these results, the study suggests that bank management should prioritize financial capital indicators by developing effective resource planning strategies and providing targeted training to enhance human resource capabilities. A focused effort on leveraging available skills, experience, and competencies is also recommended. Additionally, improving the efficiency of invested capital to optimize asset utilization and better manage liabilities is crucial. The study further emphasizes the importance of considering external environmental factors in the banking sector to strengthen overall financial performance

The research aims to analyze the causal relationship between renewable energy, foreign direct investment and economic growth in India for the period 2000–2024. The results showed a causal relationship from economic growth towards renewable energy, meaning that the expansion of economic activity was a catalyst for the development of the clean energy sector. It was also found that there is a causal relationship between renewable energy and foreign direct investment, which reflects the role of the transition to clean energy as a factor attracting international investment. However, the relationship between foreign investment and economic growth did not appear morally in the short term, which indicates that the impact of foreign investment needs more time to appear. The study concluded that India has succeeded in creating a positive link between economic development and environmental policies Promoting investments in renewable energy represents a sustainable path to support economic growth in the long term

The study primarily aims to estimate the impact of foreign trade, exports, and imports on the Gross Domestic Product (GDP) of Iraq and other Arab countries, and to demonstrate the importance of foreign trade in economic growth. It also reviews the development of foreign trade for the Arab economies under study for the period (1990-2024). This study also includes a quantitative analysis of the available economic data for the sample countries, with a focus on the relationship between foreign trade and economic growth by tracking the path of temporal changes that have occurred in the foreign trade of these countries and linking it to economic growth and other commercial events.

The main objective of this research is to clarify the research problem by answering the following key question: What role do virtual libraries play in marketing the scientific outputs of universities? The study also aims to highlight several objectives, including developing a theoretical framework that covers the concept of virtual libraries and their modern roles, proposing a hypothetical model that identifies the main sub-dimensions of the research variables, and measuring the extent to which virtual libraries contribute to enhancing access to scientific outputs.
The descriptive-analytical method was adopted, along with its techniques to obtain the required data for the study. Data were collected using a suitable questionnaire designed according to scientific standards for questionnaire preparation. The questionnaire consisted of three sections: the first focused on demographic information, the second included variables measuring the dimensions of virtual libraries, and the third addressed the variable of marketing scientific outputs.
A questionnaire was prepared in line with the research objectives and distributed to a selected sample of faculty members from the chosen population. A total of (120) questionnaires were distributed, of which (98) were returned and valid for review, while (94) were suitable for statistical analysis. The collected data were analyzed using the statistical software (SPSS V23) and (AMOS V21), in addition to applying several statistical methods such as linear regression models, mean, and standard deviation.
The research reached several key findings. The results related to the virtual libraries variable indicated a high overall level of agreement, with a mean score of (3.89), which is higher than the standard mean of (3). This reflects the interest of the surveyed universities in virtual libraries. The results of the linear regression analysis also showed a statistically significant effect of digital libraries on marketing scientific outputs. This confirms the importance of providing a digital environment in university libraries, along with various services offered by virtual libraries, such as virtual reference services, online catalog services, internet access services, and electronic collections. The diversity and integration of these services contribute to organizing and enhancing interaction and exchange between service providers in virtual libraries and users of scientific outputs, ultimately leading to better marketing of these outputs

Predictive modeling is essential for accurate forecasting across many fields but traditional regression models and most machine learning algorithms often struggle with complex nonlinear or imprecise data Generalized Regression Neural Networks GRNNs offer a promising solution yet methods for applying them to uncertain or fuzzy datasets are not well established The study develops a GRNN model which effectively handles fuzzy data The study develops a GRNN model which effectively handles fuzzy data The study develops a GRNN model which effectively handles fuzzy data The study develops a GRNN model which effectively handles fuzzy data The study employs a GRNN to predict outputs using a non-iterative kernel-based approach with input pattern summation and output layers The pattern layer calculates Gaussian-weighted distances between inputs and training samples while the summation layer aggregates these to produce predictions Fuzzy set theory enables the handling of imprecise data through its system which permits inputs and outputs to possess partial membership values The Fuzzy-GRNN framework combines GRNN predictive accuracy with fuzzy logic interpretability for regression tasks which involve uncertain or noisy data The study demonstrates that the Fuzzy GRNN model outperforms the conventional GRNN in predicting NOx levels achieving lower RMSE and MAE values The network uses fuzzy logic to model nonlinear data patterns while it handles the uncertainty present in the data The Fuzzy GRNN offers better accuracy and reliability for nonlinear regression and environmental forecasting tasks

Drinking water quality assessment is essential for protecting public health and ensuring sustainable water resources. Accurate modeling of key indicators such as Total Dissolved Solids (TDS) remains challenging due to complex interactions among hydro chemical parameters. Reliable prediction of Total Dissolved Solids (TDS) is critical for quantitative assessment of drinking water quality. This study presents a statistically grounded framework using Twin Support Vector Regression (TSVR) for modeling TDS as a function of multiple hydro chemical indicators. Both linear and kernel-based TSVR models, including Polynomial and Radial Basis Function (RBF) kernels, are formulated and systematically optimized via hyperparameter tuning to minimize prediction error. Model performance is evaluated on real-world water quality datasets using standard statistical metrics, including mean squared error and coefficient of determination. Results indicate that Linear TSVR provides optimal generalization with minimal computational complexity, whereas RBF-TSVR effectively captures nonlinear dependencies among hydro chemical parameters. These findings confirm that TSVR constitutes a statistically efficient and computationally tractable alternative to classical Support Vector Regression, offering guidance for kernel selection, hyperparameter calibration, and robust predictive modeling in water quality assessment

The research seeks to highlight the problems of measuring human capital in governmental service units in light of strategic objectives from a cost perspective, with the Nineveh Sewerage Directorate selected as a field for practical application. The importance of the research stems from the significance of human capital as one of the most important components of intellectual capital and the main factor in achieving efficiency and development in service units, as well as its role in achieving long-term strategic objectives. Based on the above, the research problem is centered on the following questions: Is it possible to measure the cost of human capital in service units, including the Nineveh Sewerage Directorate, in light of the strategic objectives pursued by the directorate? Are there difficulties in the process of measuring and determining human capital costs under these objectives?
To answer these questions, the research adopted the descriptive approach through reviewing relevant literature and previous studies, in addition to the practical aspect represented by field visits to the Nineveh Sewerage Directorate and the analysis of its data during the study period. The study concluded that measuring human capital costs requires accurate identification of the elements related to human resources using cost accounting methods appropriate to the nature of the service activity. The findings also revealed that the difficulties of measurement involve accounting, administrative, and economic dimensions, which necessitates an integrated approach to addressing these challenges. Furthermore, the study showed that estimating the replacement cost and fair value of the human workforce in the directorate reflects an added economic value resulting from accumulated experience, learning, and creativity, which contributes to enhancing the unit’s ability to achieve its strategic objectives

This study looks at how two modern accounting tools, CVFS (Cost-Value Flow Stream) and OBA (Open-Book Accounting), can help factories cut down expenses and work better. To test this, we studied the Azet Plastic Factory in Erbil using their real financial data from the fiscal year 2024. We found that old, traditional accounting methods do not work well in modern production because they hide waste and give wrong product costs. However, when the factory uses CVFS, it can easily see and stop waste inside the production lines, and when it uses OBA, it shares cost information with suppliers to build trust and lower costs between companies. Therefore, the study suggests that manufacturing factories in Erbil should stop using old accounting ways and switch to these modern tools to save money without losing product quality