Empirical research about the impact of leadership approaches on the employee motivation and loyalty

Leadership is vital in every organization. Leadership involves directing a team and communicating it to people, motivating and inspiring them to contribute to achieving organizational success. Leadership requires being strategically focused and applying behavioral techniques to build commitment and get the best work from employees. Successful leaders in business are positive, reliable and exhibit proactive attitudes, determine a vision for business goals, demonstrate a firm commitment to achieve defined goals, are able to effectively communicate their vision, teams, and organizations that are affiliated with the strategies in the planning and development of skilled, motivated, focused, and able to set clear instructions to team members dealing with the needs and opinions of the employees who was able to inspire the team to achieve goals. In today's competitive world, it is difficult for an organization to compete and even survive without satisfying the organization's most valuable asset and revealing employees' loyalty to their leaders and organizations. Therefore, the study of employee loyalty and motivation from the perspectives of leadership styles is central to this research. In other words, the purpose of this study is to investigate the impact of leadership styles on employee motivation and commitment as a predictor of group or organizational performance. A four-part questionnaire was used for different variables of the study. In the first part of the survey, the demographic information, in the second part, the Organizational Commitment Scale, in the third part, the Multi-Factor Leadership Styles Scale, and in the fourth part, the Employee Motivation Scale are included. The data obtained from the research was transferred to SPSS 22 program and analyzed. Here, frequency distributions related to the results obtained from the questions were calculated in each section. Frequency tables showed distributions and percentages of answers to questions. After that, Independent Group t-test and one-way variance analysis (ANOVA) were used to measure the impact of demographic data on scales, and Pearson correlation analysis was used to measure the relationship between scales.