Retiring on Time or Quitting Early? Preferred Retirement Age and Turnover Intentions Relationship with Organization, Team, and Individual Variables
Abstract
This thesis aims to investigate the dependent variables of preferred retirement age and turnoverintentions. The relevance of retirement age in Norway stems from the country's agingpopulation and the projected future workforce shortage. Turnover intentions refer to anindividual's desire to leave their current job in the near future. The thesis focuses on identifyingthe independent variables that predict preferred retirement age and turnover intentions. Toachieve this, a model was developed, categorizing the variables into three dimensions:Organizational, Team, and Individual levels.The analysis utilizes a dataset collected from 1531 participants, which is consideredrepresentative of the Norwegian workforce. The data's reliability and validity have beenestablished through prior research, and our factor and reliability analysis further confirmed this.To examine the relationship between the dependent and independent variables, bivariatecorrelation and multiple hierarchical regression analyses were conducted. The results revealeda strong negative correlation between turnover intentions and preferred retirement age,indicating that individuals with a higher preferred retirement age exhibit fewer turnoverintentions.In the analysis of preferred retirement age, the correlation analysis indicated a strongrelationship between certain individual variables and an increase in retirement age.Specifically, supportive leadership, autonomy, cognitive demands, social support, and agewere confirmed as significant predictors of higher retirement age. In the multiple regressionanalysis, all these variables were found to be significant in step 1, except for autonomy inworking methods and social support (which were not included in the model). However, in steptwo, all variables lost their significance. Consequently, these hypotheses are consideredpartially supported.When examining turnover intentions, the correlation analysis revealed a robust associationamong various independent variables. Specifically, emotional demands, quantitative demands,learning demands, age discrimination, negative acts, exhaustion, mental distance, emotionalimpairment, and cognitive impairment were all identified as significant predictors of increasedturnover intentions. In the subsequent multiple regression analysis, quantitative demands,negative acts, exhaustion, mental distance, and health remained significant in step 3.Conversely, we identified autonomy in working methods and working time, supportiveleadership, social support, and age as significant predictors of lower turnover intentions. Thesevariables exhibited a strong negative correlation and maintained their significance in step 3 ofthe multiple regression analysis.