Designing a Reemployment Model for Retired Education Personnel with a Mixed Approach
Abstract
Objective: This research aims to design a reemployment model for retired education personnel using a mixed approach.
Method: The present study is mixed-methods in nature. The qualitative research method involves grounded theory, and the quantitative part employs a structural interpretative method. The qualitative participants include decision-makers and policymakers in the field of retiree reemployment, along with some teachers, totaling 12 individuals. The quantitative research method uses a structural interpretive approach with a matrix of cross-impact analysis coefficients.
Findings: The qualitative data analysis encompasses 8 dimensions including individual, social, organizational, environmental, economic, political factors, individual performance, and the performance of the education system, with 23 components in the form of causal conditions, central phenomena, strategies, outcomes, intervening conditions, and contexts. The quantitative findings indicate that dependent variables such as basic and material needs, relational and emotional needs, psychological needs, psychological health, social development, and educational structure are mostly influenced by other factors. Livelihood-based strategy, job characteristics, quality of life improvement are among the independent variables. Influential variables include entrepreneurial strategy, stakeholders, support policies, educational design policies, and economic budget allocation, which are key variables for the reemployment of retired education personnel. The linking variables have a high degree of influence and dependency, which this research has not identified as a binary variable.
Conclusion: Supportive policies play a significant role in enhancing reemployment opportunities for retired education personnel, thus, supporting retirees seeking reemployment requires policies from policymakers in this area.
Downloads
Additional Files
Published
Issue
Section
License
Copyright (c) 2023 Fatemeh Bina Baji , Hamid Rezaei Far, Mohammad Mohammadi, Monireh Salehnia (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.