journal of Economics And Administrative Sciences

This paper aims to analyze the relationship and influence between strategic intelligence and its dimensions (foresight, systems thinking, future vision, and motivation) and organizational conflict management (Avoidance, Collaboration, Settlement, Competition, and Waiver) at the University of Mosul. The research problem arose from variation in organizational conflict management across the university’s colleges and the scarcity of studies examining the relationship between these two variables. The study adopted a descriptive-analytical approach, using a questionnaire as the primary data collection tool. The research population comprised administrative and academic leaders from several colleges within the University of Mosul. One hundred and forty questionnaires were distributed using stratified random sampling, of which 103 were received and deemed valid for statistical analysis. SPSS version 24 and AMOS version 24 were used to analyze the data and test the research hypotheses, employing correlation and regression methods. The results demonstrated a strong, positive, and statistically significant correlation between strategic intelligence and organizational conflict management, with a correlation coefficient of 0.80 at the 0.005 significance level. Regression analysis further demonstrated a significant positive effect of strategic intelligence on organizational conflict management. The regression coefficient was β = 0.684 (P = 0.002), and the coefficient of determination (R2 ) was 0.64. This indicates that strategic intelligence explains 64% of the observed changes in organizational conflict management. The significance of this research lies in its focus on a relatively recent topic and its contribution to enhancing university performance and improving the organizational work environment.

This study aims to investigate the role of regulatory immunity in enhancing strategic superiority from the perspective of supervisors working at the Team Mart Chain in Erbil, Iraq. Understand the notion of regulatory immunity by demonstrating the relationship and influence of the independent variable and its dimensions (organizational learning, memory, and DNA) in strategic superiority. To address the research problem, the following question was examined: to what extent does regulatory immunity contribute to strengthening strategic superiority? However, to acquire empirical data, the researchers created their own survey questionnaire. Empirical data were evaluated using a variety of statistical methods to test the research model and major hypotheses using statistical package programs (SPSS V.24). In Erbil Governorate, total of 216 supervisors from the Team Mart chain were invited to participate in the study, and 171 valid questionnaires were returned, representing a response rate of 79%.. The empirical analysis demonstrates a statistically significant positive correlation between regulatory immunity and strategic superiority. Within this framework, organizational memory emerges as the most dynamic mechanism for facilitating immediate regulatory adaptation. The findings imply that firms might achieve strategic superiority by aligning their DNA with the current regulatory framework. Companies build systemic resilience into their identities by aligning key governance mechanisms with institutional expectations. Furthermore, finding an appropriate balance between short-term adaptive learning and long-term structural stability, aided by organizational memory, is critical for maintaining a competitive advantage.

In the context of the Fourth Industrial Revolution, technological empowerment has become a strategic and existential necessity for organizations striving for growth and continued competitiveness, particularly private universities, which face significant challenges in comprehensive digital transformation. Literature reveals the absence of an integrated model linking the three research variables (technological empowerment, strategic readiness, and digital transformation). This paper aimed to examine the mediating role of digital transformation in the impact of technological empowerment on strategic readiness in Iraqi private universities. The study has employed a descriptive analytical approach, utilizing a questionnaire as the primary data collection tool. The questionnaire was distributed to 142 individuals, including university presidents, faculty members, and middle management administrative staff. The results revealed a statistically significant impact of technological empowerment on both strategic readiness and digital transformation. Additionally, the results demonstrated the effective role of digital transformation in enhancing strategic readiness and its function as a mediating variable, facilitating the transmission of influence (both directly and indirectly) between technological empowerment and strategic readiness. The paper concludes that the relationship between the three variables is complementary, with digital transformation playing a pivotal mediating role. Technological empowerment is the strategic foundation for the success of digital transformation. The paper recommends investing in technological empowerment as a comprehensive strategic approach and adopting a clear vision for decision-makers that links technology and strategy to ensure a sustainable competitive advantage for Iraqi private universities.

This study uses an econometric approach to examine how sustainability indicators affect agricultural output in Iraq. Water sustainability, food security sustainability, the agricultural labor force, and virtual water imports are independent variables, and agricultural output is the dependent variable. The analysis uses annual data from 1990 to 2024. The Autoregressive Distributed Lag (ARDL) model is applied to analyze both short- and long-run relationships. Specifically, the results confirm the existence of a long-run equilibrium relationship between sustainability indicators and agricultural output. In the long run, water sustainability positively affects agricultural output, indicating a direct, expected relationship. Furthermore, food security sustainability has a positive, statistically significant impact at the 1% level. In contrast, the agricultural labor force variable shows a negative, statistically insignificant coefficient, which may reflect the prevalence of disguised and seasonal unemployment in the agricultural sector. Meanwhile, virtual water imports have a negative and statistically significant effect, consistent with theoretical expectations. These findings support the hypothesis that sustainability indicators significantly influence agricultural output, although the magnitude and direction of effects vary across dimensions.

The paper aims to analyze the determinants of virtual water use for barley crops in Iraq over the period (1990–2023), in light of increasing water challenges and declining inflows of the Tigris and Euphrates Rivers. The research adopts a descriptive and econometric analytical approach, employing the Autoregressive Distributed Lag (ARDL) model to examine the relationship between imported virtual water quantity (VW) as the dependent variable and a set of independent variables, including agricultural GDP, blue water, the water self-sufficiency ratio, and the degree of agricultural trade openness. The results of the Bounds Test indicate the existence of a long-run equilibrium relationship among the variables. Furthermore, the Error Correction Model (ECM) reveals an effective adjustment mechanism, with an adjustment speed of 72% annually, indicating convergence toward the long-run equilibrium path. The findings also demonstrate significant, albeit varying, effects: agricultural GDP and the water self-sufficiency ratio exhibit an inverse relationship with virtual water imports, whereas trade openness and green water show a positive relationship with virtual water imports. The study recommends adopting water-oriented trade policies that support domestic production and improve the efficient use of available water resources, with the aim of reducing reliance on imports of waterintensive commodities. It also emphasizes the importance of adopting the concept of virtual water as a fundamental basis for formulating agricultural foreign trade policies.

This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algorithm tunes the smoother factor (l) and the control boundary (L) at a certain sample size to minimize the Average Run Length (ARL) of the nonparametric exponentially weighted moving average (NPEWMA-SR) scheme. Third, the framework is validated via R software. The framework was applied to Google’s daily trading data using different sample sizes (10, 30, 60, 120, 250, 365, 600, 900, and 1245) days of 2026, to detect the shift in the system, within 2 trading days, achieving an In-control Average Run Length ARL0 = 499.6 and an Out-of-control Average Run Length ARL1 = 1.65 days. The system demonstrated high statistical stability, a very low false alarm rate, and the best statistical sensitivity among all sample sizes. These results prove its effectiveness across small, medium, and large samples, making it a powerful early warning system for monitoring market volatility.

This paper aims to assess the environmental performance of the industrial sector, using the Kufa Cement Plant as a case study due to the tangible environmental impacts of this activity in the areas of gaseous and dust emissions, energy consumption, and waste management. It emphasizes the importance of adopting systematic assessment tools that align with sustainability frameworks and local and international regulations. This research employs a descriptive-analytical methodology, based on the theoretical framework for environmental performance assessment and the principles of environmental management, utilizing performance indicators derived from the international standard ISO 14031 to analyze the plant’s operational and environmental data. The results showed a relative improvement in indicators for controlling solid pollutants, but revealed the persistence of significant challenges related to gaseous emissions and energy intensity. The study concluded that adopting integrated environmental management systems is a pivotal factor in improving performance and mitigating environmental impacts. It recommended investing in clean technologies, strengthening monitoring mechanisms, and integrating environmental considerations into management decision-making processes to ensure improved efficiency and support industrial sustainability. This work offers a valuable practical contribution by presenting a practical model based on international standards for assessing environmental performance in heavy industries within a local context.

The objective of this paper is to investigate the effect of the earnings ratio and capital structure on share price, with special focus on the moderating role of free cash flow (FCF) in the manufacturing sector listed on the Iraqi Stock Exchange (ISX) for the period 2016 to 2023. Using a quantitative research method, the study draws data from audited financial statements, including the income statement, balance sheet, and cash flow statement, and analyzes 10 manufacturing companies over eight years. The analysis employs a regression model, descriptive statistics, correlation analysis, ANOVA, and tests of cross-sectional dependence and non-stationarity to ensure diagnostic robustness of the results. The findings reveal that ROA has a statistically significant positive effect on share price, suggesting that investors reward companies that use their assets efficiently to generate profits, whereas ROE shows an insignificant negative correlation with share price, indicating that higher equity returns do not necessarily translate into higher market valuations, possibly due to investor concerns or external economic conditions. Regarding capital structure, DER demonstrates a positive relationship with stock prices, implying that moderate levels of debt may signal confidence and growth potential, while DAR has a negative effect, reflecting investor caution toward firms with high levels of total debt. Interestingly, the moderating role of FCF produces similar results in some variables, suggesting that although FCF is important, its effects may be different. This study is limited to the manufacturing sector on the Iraqi Stock Exchange and future research may explore its other sectors.