Abstract

The protean career concept is dominating recent career research. Demographic groups are postulated to differ on protean career behavior with implications for career development, social equity and management of an increasingly diversified workforce. The purpose of this paper is to explore the unique contributions of employees’ gender, nationality, sector and age in the deployment of career advancement strategies in the high demographic inequality labor market of Kuwait. This is one of the few studies with an exclusive focus on demographic differences in protean behavior. Most protean career research treats demographic difference as an ancillary focus, even though demographic differences are part of the foundation of psychological sciences. The study utilized a set of questionnaires on a sample of 908 highly educated young employees working in Kuwait. Primary findings are that there are greater demographic differences in protean career in Kuwait than in the West. Men, Kuwaitis, private sector and younger employees deploy significantly more career advancement strategies and have stronger strategy orientations than women, self-initiated expatriates (SIEs), civil servants and older employees. The results are attributed to contextual inequalities in opportunities because they echo the Kuwaiti segmented labor market by gender, nationality and sector. They also reveal that women’s and SIEs’ proactive career histories have not been sustained in the Kuwaiti workplace. These demographic differences in protean behavior suggest that the potential benefits of this behavior are limited to members of particular groups, and any intervention strategies to support career development may, therefore, benefit a large portion of the workforce that is impacted by the inequalities. The originality and value of this study stems from addressing four literature gaps. Specifically, it examines the understudied protean behavior as most studies have focused on attitudes. It centers on demographic differences in protean career behavior, utilizes native and SIE samples working in high inequality non-Western context.

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