AI Summary & Key Takeaways
AI InsightAs an application of the proposed model the results in this paper have been illustrated by using data from a recent survey among the staff members of the University of Southern Queensland, Australia.
📌 3 Key Takeaways
Abstract
Mobility models are very useful in explaining the movements of people over socio-economic and job categories. Occupational mobility deals with the movements of individuals over job categories during their employment periods. Since the time interval between successive job changes is a random variable, different occupational mobility models have been developed by scientists using modified Markov and semi-Markov processes. This phenomenon can be modelled by considering the underlying factors such as job satisfaction, salary, distance of the work place, family requirements and others. Unlike most of the previous works in this area, the present study suggests a new measure of occupational mobility based on the distribution of wages. Here a general occupational mobility model has been developed to study the pattern of mobility during the service life of employees. First the probability distribution of the number of job changes in the entire employment life of individuals has been obtained considering the inter-job offer times (within an interval) and the associated wages as random variables. Then a measure of occupational mobility based on this distribution has been developed. The results are obtained under both frequentist and Bayesian frameworks. As an application of the proposed model the results in this paper have been illustrated by using data from a recent survey among the staff members of the University of Southern Queensland, Australia.