Carlos-María Alcover, D. Guglielmi, M. Depolo, G. Mazzetti
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引用次数: 9
Abstract
As the aging population and workforce constitute a worldwide concern, it is becoming necessary to predict how the dual threat of aging and technology at work increases the job vulnerability of older workers and jeopardizes their employability and permanence in the labor market. The objective of this paper is twofold: (1) to analyze perceptions of artificial intelligence, robotics, and automation in work settings and the expected impact of these technologies on older workers to contextualize this emergent phenomenon; and (2) to propose a general model related to “Aging-and-Tech Job Vulnerability” to explain and predict the combined effect of aging and AI/robotics/automation on job insecurity and additional outcomes among older workers. The propositions of the Age-and-Tech Job Vulnerability model developed in this paper seek to present a first approach for the conceptual advance and research on this emerging phenomenon and entails several theoretical and practical implications for organizational psychology.
期刊介绍:
Organizational Psychology Review is a quarterly, peer-reviewed scholarly journal published by SAGE in partnership with the European Association of Work and Organizational Psychology. Organizational Psychology Review’s unique aim is to publish original conceptual work and meta-analyses in the field of organizational psychology (broadly defined to include applied psychology, industrial psychology, occupational psychology, organizational behavior, personnel psychology, and work psychology).Articles accepted for publication in Organizational Psychology Review will have the potential to have a major impact on research and practice in organizational psychology. They will offer analyses worth citing, worth following up on in primary research, and worth considering as a basis for applied managerial practice. As such, these should be contributions that move beyond straight forward reviews of the existing literature by developing new theory and insights. At the same time, however, they should be well-grounded in the state of the art and the empirical knowledge base, providing a good mix of a firm empirical and theoretical basis and exciting new ideas.