Using Big Data to test labor market stability vs dynamism: what career path leads to better outcomes

Abstract

In recent decades, longstanding questions that have been broadly debated in the career management literature, remain unresolved: are careers becoming dynamic or stable, which leads to how to optimize career progress–via dynamic moves or stable employment. We address conflicting findings and aim to advance career theory in three ways. Theoretically, we offer empirical support for both boundaryless career and career ecosystem theories and expand the career ecosystem theory and provide new evidence to key scholarly debates regarding new careers. We offer practical advice to individuals regarding their career strategy. Utilizing an extensive database of 3,000,000 individuals, comprising one country’s entire working population, and their 300,000 employers, we find support for a dynamic labor market characterized by three different career boundary crossings: job, employer, and sector change across eleven years. We identify distinctive clusters of career transitions that we associate with career outcomes. We find a moderating effect of birth cohort, the share of stayers, leavers, managerial and professional employees, firm size, and gender, and differences between the impact of boundary-crossing and both wage level and wage growth, with contrasting patterns for each. We demonstrate that in most cases, opting for frequent career moves would offer better outcomes compared to stable employment. The theoretical contribution and their implications for our understanding of career motives and career dynamism are discussed.