journal of Economics And Administrative Sciences

Abstract:
The present study analyses the impact of dynamic capabilities on the high performance that can be developed in administrative units under the Anbar Governorate of Iraq. Sensing, learning, coordinating, and integrating capabilities are dynamic capabilities that actually represent the organization's capacity to adjust itself to changing environments and its sustainable growth. High-performance organization could be reflected through continuous improvement, quality management, excellence in human resources, orientation, and commitment, considering it the measures of organizational effectiveness in reaching strategic objectives.
Research shows that the dynamic capabilities and high performance of the administrative units studied were at moderate levels. The results of the findings disclosed the existence of a significant positive relationship between dynamic capabilities and high performance, since it was revealed that dynamic capabilities such as proactive sensing of opportunities and challenges, coordinated efforts, and continuous learning directly improve organizational performance outcomes.
Along this line, therefore, this highlights the importance of developing dynamic capabilities by focusing administrative units' attention on training, resource integration, innovative practices, and the like. Exploring some of the issues concerning these unit's limited coordination and learning will improve organizational adaptability through better resource utilization and improved service delivery to their local communities, thereby enhancing high performance.

Abstract:
The present study investigates the linkage between strategic leadership practices and quality of work life (QWL) within the Intelligence and Counter-Terrorism Directorate. Data was drawn from 115 freshly acquired respondents from senior and middle management by means of a multi-item questionnaire. The analysis that follows - SPSS, AMOS and SMART PLS V.4 - shows that the Directorate's clear defining of strategic direction and decisive decision making largely affects QWL. The study deduces critical issues pertaining to strategic leadership towards the improvement of work conditions and job security and human capital development where all will lead to better performance by the organization. In summary, strategic leadership practices, including setting strategic direction, developing human capital, ethical practices, and balanced strategic control, significantly affect quality of work life. The Directorate is very much interested in a clear definition of direction with respect to the strategic direction resulting from its decisive and bold decision-making at several points of the organization and with its transparent task descriptions. The Directorate also shows increasing importance toward emphasizing ethical practices by backing its levels with some ethical standards and principles and proper use of scarce resources in tandem with the Directorate approach towards further showing interest in the constitutionality of how the work is arranged, dealing equally with workers, and providing job security based on efficiency and productivity. This study, therefore, emphasizes the relevance of strategic leadership with respect to the positive creation of an atmosphere within which to improve organizational performance through better quality of work life.

Abstract:
This paper investigates the effect of motivation leadership on the performance of succession planning in the Ministry of Education / the First Rusafa Education/ Baghdad. The data was collected for the employees, which was analyzed using the inspirational leadership model. Other dimensions like creating inspiration for followers, future vision, communication, teamwork and mutual trust are also emphasized. The study shows that in order to realize optimal results, there needs to be constant support and supervision from the management. There were problems that were traced in the internal communication that led to this phenomenon. The role of an inspiring leader who is able to utilize the cognitive and behavioral capabilities of an individual to achieve the desired goal of the organization is very important. The research also points out that there is a great need for effective succession planning which aimed at nurturing and retaining talent within the organization. This accomplishment, together with the trained staff who are capable of making decisions that will take into consideration all the cognitive and behavioral capabilities that the organization can offer. This blended approach looks at improving overall performance and reaching organizational goals in the long term.

This research explores psychological capitals influence on professional compatibility among its employees in the General Directorate for Administrative Affairs, Ministry of Education, Iraq. Psychological states include self-efficacy, optimism, hope, and flexibility, which are essential in preparing employees so they can adjust accordingly to their professional roles. In addition, it will examine professional compatibility through some of its dimensions such as the nature of work, work environment, relationships with colleagues, and relationships with supervisors.
The research showed a strong impact of positive psychological characteristics, including a proactive attitude and resilience, in the adaptability of an individual in the diversity of workplace challenges and alignment with the objectives of the organization. Moderate levels of psychological capital among employees with a combination of inadequate managerial support and dissatisfaction with the work environment inhibited the actualization of professional compatibility.
Emphasis on the study has been put forward for developing psychological capital through improved managerial practices such as open communication, participatory decision making, and a support-the-work environment. This is very vital for effective improvement in employee integration, satisfaction, and ultimately performance, which is expected to strengthen the overall effectiveness of the organization to accomplish its goals.

This research study investigates the impact of organizational immunity on the attainment of institutional excellence at the Oil Products Distribution Company of the Iraqi Ministry of Oil. The components that encapsulate organizational immunity include but are not limited to organizational learning, organizational memory, and organizational DNA, which together empower the organization for adaptive response in the face of challenges and the resilience to bounce back. From here, an institution is expected to demonstrate excellence in leadership, in human resources, in service quality, and in organizational culture.
The study further states that there is a positive significant relationship between the tenets of organizational immunity and institutional excellence. Thus, enhanced institutional immunity creates institutional resilience, which enables taking care of stability, adaptability to the environment, and sustainable competitive advantage. Results show that organization learning and memory contribute significantly to institutional excellence in building the retention and adaptability of knowledge in the pro-active response to challenges.
The study, therefore, emphasizes the need for improving organizational learning through continuous development programs and using organizational memory to ensure consistency within decision-making and operational success. It also underscores the importance of culture-building on resilience and adaptability toward creating institutional excellence sustainable over time and positioning the organization for competitive advantage and growth.

This paper describes the financial performance of the banking sector in Iraq using the PATROL early warning model. The research found the strengths and weaknesses in bank operations and forecasted the financial crises using data from 2018 to 2022 to enhance performance. The indicators included capital adequacy, credit risk, profitability, organizational efficiency, and liquidity, with performance rated on a scale from "very good" to "poor." Related findings proved that the Iraqi banks would be entirely successful in financial performance regarding most indicators and scaling-high in capital adequacy, profitability, organization, and liquidity, in accordance with sound management and robust operations. However, credit risk posed challenges because the assets demonstrated lower quality compared to other indicators. Findings from the research suggest the importance of the PATROL model in guiding regulatory authorities in monitoring financial health, correcting imbalances, and improving stability. Overall, the empirical study tends to validate the effectiveness of the model as a strategy for improving and assessing financial outcomes in the banking sector.
The research study has been geared towards the analysis of the financial performance of the banking sector in Iraq using the PATROL early warning model. The research found strengths and weaknesses in bank operations and predicted the financial crises using data from the years 2018 to 2022 to enhance performance. The indicators included capital adequacy, credit risk, profitability, organizational efficiency, and liquidity which were rated with respect to performance on a scale from "very good" to "poor." Related findings proved that the Iraqi banks would be entirely successful in financial performance regarding most indicators and scaling-high: capital adequacy, profitability, organization, and liquidity according to sound management and robust operations. However, credit risk posed challenges, which showed lower quality assets compared to other metrics. The research points out the usefulness of the PATROL model in guiding regulatory authorities to monitor the financial health, correct imbalances, and improve stability. In general, the empirical study seems to affirm the efficacy of the model as a scheme for assessing and improving financial outcomes not just for the banking sector, but for all sectors.

The study scrutinizes the influence that industrial investment has on unemployment rates in Iraq during the years ranging from 2004 to 2022. Employing the ARDL econometric model, the study analyzes and interprets the net as well as foreign investments and their concomitant relationship with unemployment. The findings reveal a significant and direct qualitative relationship between investment in the industrial sector and unemployment, showing that increased investment in this sector will, indeed, decrease the unemployment level. This has managed to emphasize the importance of an industrial sector in the absorption of surplus labor and contributions to gross domestic product (GDP). Further, by establishing a local industry that meets national demand of goods and services, investment in the industrial sector will have an alternative to imports and be able to stabilize the economy while improving growth. The latter includes the standpoint that efficient public spending would, therefore, be maximized by the industrial sector in terms of economic development and employment. Also, the study will emphasize how a stable investment environment can thus be used to attract local and foreign investments by having political, economic, and social stability. The results also show that bureaucracy clearing, enhancement of physical infrastructure, and legal guarantees and incentives form an important list of things that encourage a conducive investment environment. Overall, the study gives an insight to contribute better understanding on how those strategic investments in the industrial sector can serve to reduce upfront unemployment and yet foster sustainable economic growth in Iraq. This study offers significant insights to many policy makers in terms of maximizing the effectiveness of public spending and investment in achieving long-term economic objectives.

This study examines how autocratic, democratic and laissez-faire styles of leadership affect employee motivation in the different directorates of the Ministry of Interior, otherwise known as Soran Independent Administration. Research has proven that such styles of leadership are going to affect the way employees engaged and committed themselves to the performance outcome for the sake of organizational success. High levels of democratic leadership or participative decision-making and inclusivity-related structures would, however, create conditions conducive to employee motivation. Recommendations for further research have been made in relation to the study variables. An additional area for further development includes the relationship between laissez-faire, leadership and employee motivation, especially pertaining to the more experienced employees. An autocratic style of leadership is associated with highly centralized decision-making and closely controlled decision environments. In this context, the style may portray itself as very little or even null in terms of motivational influence on employees. This negative emphasis often goes along with lowered creativity and less engagement by the employees with work. These findings indicate the need for anchoring leadership styles under a banner of a scope that should create the entire base of guidelines on open communication trust and employee empowerment as a more strategic approach to better employee motivation and improved organizational outputs. Indeed, by applying participative and autonomous leadership approaches to organizations, such factors become important in creating an environment really conducive to innovation, loyalty, and productivity. Its outcomes point out leadership strategies that can be optimized for effective employee motivation and remind organizations about the practical ways to move toward developmental success.

This article aims to discover the influence of Electronic word of mouth (eWOM) on consumer purchase intentions within the context of TikTok Shop, with particular attention given to household products. The motivation behind this study is to explain key variables that determine the role of eWOM as a major driver of consumer behavior in the digital market. A detailed model was also recommended to clearly establish how information perceived as useful and reader attitudes towards shared content influence purchasing behaviors. Conducting a mixed-methods investigation, this study aims at collecting the necessary data on 500 consumers from Ho Chi Minh City, then analyzing it via SPSS 24 and SmartPLS 4. The findings indicate the mediating effect of the acceptance of eWOM, its high impact on purchase intentions, as well as its relation to a great many other variables. These discoveries could guide some corporate strategies aimed at enhancing eWOM for maximum customer engagement on the worldwide stage for competitive marketing.

The enhancement of predictive accuracy of the first-order integer autoregressive (INAR 1) model is the focus of the study through the effective amalgam of machine learning techniques and classical statistics. INAR (1) model structures are key elements for the prediction of nonnegative integer-valued time series processes. Conventional estimation methods include Classical Least Squares (CLS), Conditional Maximum Likelihood (CML), and Yule-Walker (YW) as compared with advanced methods like Support Vector Regression (SVR) and Genetic Algorithms (GA). A new clustering algorithm was created (with SVR to GA) to determine optimal INAR (1) model parameters. Computer simulation studies confirmed the effectiveness of the INAR-SVR and INAR-SVR-GA models compared to traditional methods.
The hybrid SVR-GA approach improved predictive accuracy by a wide margin, particularly with higher parameter values. This highlighted the robust performance of the SVR-GA-CML model, exhibiting uniform lending credibility at more diverse sample sizes and parameters. Integration of artificial intelligence into traditional statistical techniques in time series forecasting has taken the superior place. Enhancing accuracy is being turned into practical areas where forecasting economics and population studies need to make decision-making and allocation decisions with precise forecasts.
The originality of this study lies in the integration of statistical and AI hybrid techniques to upgrade the accuracy of time series forecasting. It provides the much-needed insight into the analysis of integer-valued time series and underscoring AI's transformational role in predictive analytics. Approval based on ethical standards was passed, and none of the contributors declared a conflict of interest.

The problem of multicollinearity among independent variables in a regression model was addressed in this study using Partial Least Squares (PLS) and Principal Component Analysis (PCA). The influence exerted by multicollinearity can deteriorate the results of regression modeling; that is, it makes the traditional technique OLS less reliable. The research is centered on applying advanced algorithms for Partial Least Squares (SIMPL and O-PLS) as well as for PCA (NIPALS and SVD) on real-life data scenarios, as well as integrating genetic algorithm (GAs) with these algorithms to optimize predictive performance.
The relative efficiency of these methods is evaluated primarily through the amplitude of the Mean Square Error (MSE) used as a criterion for comparison. The results show the effectiveness of PLS-OPLS above PCA in terms of the lowest before and after embedding genetic algorithms into the MSE. All this underpins the effectiveness of PLS in minimizing multicollinearity thereby allowing for the formulation and prediction of very highly predictive models.
More and more indication of subtle class was revealed with regard to fine tuning advanced GA technique in favor of enhancing regression modeling for complex data analysis. The ongoing research will help in opening numerous possibilities to reinforce regression methodology, especially when one factor in an array of applications representing a relatively significant level of prediction accuracy.

The purpose of our research is to work to maintain parameters for the Gamma Distribution within a better frame of precision in the context of other methods and dealing with outliers. Outliers are common and pose a threat to modelling because one little outlier scales a statistical model and brings about the estimations of parametric index validity. The objective of this study was to find useful applications for the detection and mitigating effect of outliers accomplished through the Hampel filter, the nonlinear fit of the Gamma distribution using the Median Rank Regression (MRR) method for the calculation of the shape parameter and scale parameters.
This study then generated simulated data drawn from various parameter values of the Gamma distribution modelled with outliers and ran through the proposed Hampel-MRR method. These results were compared with those produced by the MLE and classical MRR methods based on MSE performance measures. From this research, it was observed that the proposed method gives a more accurate and robust estimate of the parameters, especially with increasing sample sizes and varying parameter values.
Implications of this research are those of broader application for the improvement of reliability research. This is just what is needed in decomposing survivability time distribution aiming to predict system performance and maintenance interventions. Superb empowerment and clubbing the years of theory with real-time applications are big draws for this technique over its counterparts in the midpoint of the era of outliers.

The paper focuses on investigating the impact on the Korean financial sphere, specifically Creative Accounting Practices (CAPs), by using the model in the paper, upon any type of AI. Included are various systems used for recording, monitoring, and reporting financial activities with AI as an intermingling agent for financial decision-making and resources management. The survey was carried out in Iraqi Carpet and Furnishing Company, where CAPs were plead to penance for their (mis-) deeds by artificially fast improvements in the appearance of the financial statements, thus eroding the trust in the adequacy and potency of the statements. The study referred to Miller's model in doing some sort of proper line-linking on the spotting as well as the interpretational section of the CAPs in company financial statements for the years 2018 to 2022. The finding asserted that CAPs in the financials of the company misled investors, sidelined its real financial performance, eroding confidence in AI, thus making the feasibility of the financial decision-making a moot front. It is crucial to establish more control and impart strict accounting standards and business ethics to ensure that there is a guarantee as to how they produce computerized financial information and mitigate the damage resulting from CAPs. This research sheds light on the understanding of the way CAP can distort the financial records and profoundly speaks for transparency in financial reporting. This research, thus, specifically conveys a message to the world about the importance of transparency and consists in writing financial reports while building trust and enforcement in ensuring accounting standards are adhered to. Last, but not least, the study lays firm emphasis on the entry of strict internal controls, instituting periodic audits, and the like, and imparting continued education to financial statement preparers to instill virtues of ethical practices in them. Through this, the study aims to widely inculcate in the spirit of honesty and accountability within most organizations, taming the risks associated with CAPs who would guarantee nothing but an accurate level of income and self-introduction of "authentic balances."