Job-to-Job Transitions and Unemployment Dynamics

Leaders, managers, professionals, and employees throughout organizations worldwide often face a large number of job transitions, many unexpected, in their careers. Job loss is widely recognized as one of life's more traumatic experiences. It is a stressful, life-changing event—one that can lead to negative mental and physical health consequences and jeopardize financial security and relationships. In addition, mid- and late-career job seekers face unique job-search issues and challenges. Career transition, however, can also be a positive event and growth opportunity, especially when one has prepared in advance for the possible personal impact of widespread organizational restructuring and downsizing. Advance preparation supports career and emotional resilience. This chapter presents challenges surrounding job loss, discusses proven strategies and processes for those in transition, and offers the research-based tool of guided imagery as a means to increase resilience, perceptions of personal control, and job search self-efficacy along with speed of reemployment.

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Long-Run Sectoral Reallocation, Job to Job Transitions, and Earnings Inequality: An Empirical Investigation

SSRN Electronic Journal ◽

10.2139/ssrn.2820610 ◽

2016 ◽

Cited By ~ 3

Author(s):

Florian Hoffmann ◽

Anton Laptiev ◽

Shouyong Shi

Keyword(s):

Empirical Investigation ◽

Earnings Inequality ◽

Job Transitions ◽

Long Run

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Involuntary Job Transitions and Subjective Well-Being

Lifecycle Events and Their Consequences ◽

10.11126/stanford/9780804785853.003.0005 ◽

2013 ◽

pp. 76-96 ◽

Cited By ~ 2

Author(s):

Ariel Kalil ◽

Thomas DeLeire

Keyword(s):

Well Being ◽

Subjective Well Being ◽

Job Transitions

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Network-driven differences in mobility and optimal transitions among automatable jobs

Royal Society Open Science ◽

10.1098/rsos.182124 ◽

2019 ◽

Vol 6 (7) ◽

pp. 182124 ◽

Cited By ~ 1

Author(s):

Jordan D. Dworkin

Keyword(s):

Network Structure ◽

Potential Benefit ◽

Network Science ◽

Job Transitions ◽

Job Growth ◽

New Jobs

The potential for widespread job automation has become an important topic of discussion in recent years, and it is thought that many American workers may need to learn new skills or transition to new jobs to maintain stable positions in the workforce. Because workers’ existing skills may make such transitions more or less difficult, the likelihood of a given job being automated only tells part of the story. As such, this study uses network science and statistics to investigate the links between jobs that arise from their necessary skills, knowledge and abilities. The resulting network structure is found to enhance the burden of automation within some sectors while lessening the burden in others. Additionally, a model is proposed for quantifying the expected benefit of specific job transitions. Its optimization reveals that the consideration of shared skills yields better transition recommendations than automatability and job growth alone. Finally, the potential benefit of increasing individual skills is quantified, with respect to facilitating both job transitions and within-occupation skill redefinition. Broadly, this study presents a framework for measuring the links between jobs and demonstrates the importance of these links for understanding the complex effects of automation.

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