Exploring Post–COVID–19 Workforce Dynamics: An Experimental Study on Factors Affecting Job Acceptance in Goa

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In the post-COVID-19 era, the dynamics of labor market participation and job acceptance have shifted significantly, driven by the development of societal and psychological factors. The study highlights the intricate interplay of psychological, societal, and economic factors influencing job acceptance in the post-pandemic labor market. It investigates the determinants of job acceptance, emphasizing the roles of risk aversion, marital status, and job attributes in Goa’s labor market. Using primary data collected from respondents aged 21-55, through stratified sampling, the study applies the Cragg Hurdle Model for analysis. Key findings reveal that job attributes, including flexible working hours, job security, commuting distance, promotion opportunities, and housing conditions, play a critical role in influencing job acceptance. Risk aversion emerged as a crucial psychological factor. Risk-averse individuals strongly preferred stable and predictable jobs, whereas risk-takers were more likely to accept positions with longer hours or fewer guarantees of security. During the pandemic, risk-averse individuals avoided roles involving higher perceived risks. Marital status positively influenced engagement, with married individuals displaying higher job acceptance rates due to the need for financial security and family stability. Marginalized groups experienced disparities in job acceptance due to socio-economic challenges and limited access to resources. Notably, job acceptance was affected by practical considerations, such as commuting time and accommodation conditions. While findings provide valuable insights into Goa’s labor market, limitations include the regional focus, which may restrict broader applicability. Policymakers should prioritize bridging the urban-rural divide and employers must design more flexible, stable, and growth-oriented roles to foster workforce engagement. Future research should employ longitudinal methods to capture changing labor market trends across wider contexts.