PREDICTING TURNOVER OF EMPLOYEES BY JOB ATTITUDE: COMBINED USE OF HIERARCHICAL CLUSTER AND PATH ANALYSIS

• Published in: Jikken shakai shinrigaku kenkyū Vol. 16; no. 1; pp. 8 - 16
• Main Author: FURUKAWA, HISATAKA
• Format: Journal Article
• Language: English
• Published: The Japanese Group Dynamics Association 1976
• ISSN: 0387-7973; 1348-6276
• DOI: 10.2130/jjesp.16.8

Employee turnover has been the subject of much practical and theoretical research because it represented important personnel and organizational problems. In the past, many studies indicated a great many variables related to employee turnover. The comprehensive review of these studies showed job satisfaction was consistently and inversely related to turnover. These studies, however, did not treat simultaneously a set of variables as a system and never discuss the interrelations among such variables. This study was based on the assumption that employee turnover would be influenced by many job attitude variables. Therefore, the author stressed the consideration of a complex system of relationships among variables. A special type of multivariate analysis method was adopted to achieve this object. That is, hierarchical cluster analysis and path analysis were used to explore the hypothesized complex linkage pattern of interrelationships among job attitudes variables. Hierarchical cluster analysis reduced the number of variables, offered hints about causal patterns, and made path analysis more practicable. The effects of job attitudes on turnover was analyzed by using data collected from 297 male workers engaged in railroad maintenance. It was found that attraction to workshop and identification with organization had direct effects on turnover. Chance of participation had a slight but direct effect on it. Group norm affected turnover indirectly through attraction to workshop and identification with organization. Also, job control affected it through chance of participation and identification with organization. In general, these findings showed that employee turnover was most closely tied to group norm and human relation variables, and supported hypothesis. Based on these findings, it was argued that the combined use of hierarchical cluster analysis and path analysis was very useful in predicting employee turnover. Finally, methodological considerations and future research needs were also discussed.