Employing Logistic Regression in Supporting Strategic Management Decisions

This study aims to highlight the role and importance of logistic regression analysis in supporting and improving strategic decision-making within organizations. In today’s complex and rapidly changing business environment, strategic decisions are often exposed to high levels of uncertainty and risk when based solely on personal judgment.\r\nThe research developed a hypothetical logistic regression model to examine the impact of several managerial variables — including leadership and decision-makers, available resources, organizational culture and institutional values, information quality, technology and innovation, market competition and pressure, and risk tolerance — on the effectiveness of strategic decisions.\r\nThe study adopted a descriptive-analytical approach using Binary Logistic Regression through SPSS Version 26 to analyze data collected from a sample of 120 administrative leaders working in Rafidain and Rasheed Banks.\r\nThe results indicated that leadership and decision-makers, available resources, information quality, technology and innovation, and risk tolerance have significant positive effects on strategic decision effectiveness, whereas organizational culture and market competition showed no statistically significant effects.\r\nThe study concludes that logistic regression provides an effective quantitative tool for analyzing complex organizational factors and estimating the probability of strategic decision success, thereby improving the efficiency and quality of strategic management decisions.\r\nThe study recommends integrating statistical analysis tools into decision support systems and training managers to interpret and apply statistical outputs effectively.\r\n