THE IMPACT OF LEADERSHIP STYLES ON EMPLOYEE PERFORMANCE IN SMES IN UZBEKISTAN
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Keywords

Keywords: Leadership styles; Employee performance; SMEs; Uzbekistan; Organizational performance.

How to Cite

Ikromova Khadicha Ikrom kizi, Heny Hendrayati, and Inomjon Qudratov. “THE IMPACT OF LEADERSHIP STYLES ON EMPLOYEE PERFORMANCE IN SMES IN UZBEKISTAN”. World Scientific Research Journal 50, no. 2 (April 25, 2026): 264–274. Accessed July 15, 2026. https://openresearch-hub.com/index.php/wsrj/article/view/1889.

Abstract

This study explores the influence of various leadership styles on the performance of employees in small and medium-sized enterprises (SMEs) in Uzbekistan. It specifically examines three leadership styles: autocratic, democratic, and laissez-faire. Employing a quantitative research design, data were gathered through a structured questionnaire distributed to 110 SME employees. The analysis of the data was conducted using statistical techniques, including descriptive statistics, correlation, and multiple regression analysis. This research investigates how different leadership styles affect employee performance within small and medium-sized enterprises (SMEs) in Uzbekistan. The study concentrates on three primary leadership styles: autocratic, democratic, and laissez-faire. A quantitative research method was employed, gathering data via a structured questionnaire given to 110 employees in SMEs. The collected data were analyzed using statistical methods, such as descriptive statistics, correlation, and multiple regression analysis. This research investigates how different leadership styles affect employee performance within small and medium-sized enterprises (SMEs) in Uzbekistan. The study concentrates on three primary leadership styles: autocratic, democratic, and laissez-faire. A quantitative research method was employed, gathering data via a structured questionnaire given to 110 employees in SMEs. The collected data were analyzed using statistical methods, such as descriptive statistics, correlation, and multiple regression analysis.

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