| In the 21st century's competitive labor market, a major problem facing organizations is employee urnover. This expensive problem can be prevented if organizations understand why employees choose to leave and what can be done to stop them from doing so. The problem this study addressed is employee turnover as measured by employees' organizational commitment and intention to leave. The purpose of this quantitative correlational study was to determine the turnover intention and the organizational commitment level of XYZ employees in relation to age, gender, and pay classification in order to provide organizations with valuable information for retaining employees. The Organizational Commitment Questionnaire (OCQ) and the Anticipated Turnover Scale (ATS) are instruments that were used to determine if there is a relationship between the intention to leave and how it relates to employee turnover for manufacturing organization employees. Participants included 117 employees of XYZ Company, a nonunion manufacturing organization in business since 1981. A significant relationship was found between the variables of organizational commitment and age in regard to an employee's turnover intention. For organizational commitment, the results of the correlation analysis indicated a significant negative relationship, r = -596, p < .001 between organizational commitment and an employee's intent to leave an organization. The results of the overall regression were significant, F(1, 115) = 17.96, p < .001. Age was a significant contributor, t = -2.45, p = .016. In addition, more than 50% of the variability in turnover intentions as not explained by the predictor variables of organizational commitment, age, gender, and pay classification. These results were significant at F(4, 112) = 17.96, p < .001. Manufacturing management, including executive managers and human resources managers, would benefit from understanding the organizational commitment levels of their employees. Additional research involving gender, pay classification, and turnover intentions for another manufacturing population would be beneficial, as would studies including variables such as employee job satisfaction, autonomy, work schedules, and pay dissatisfaction, and how they relate to an employee's intent to leave. |
