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Never too late to learn: Unlocking the potential of aging workforce in manufacturing and service industries

Thilini Ranasinghe, Eric H. Grosse, Christoph H. Glock and Mohamad Y. Jaber

International Journal of Production Economics, 2024, vol. 270, issue C

Abstract: This study systematically reviews 51 articles from Scopus and Web of Science databases to investigate the learning of aging workers in the manufacturing and service industries. It focuses on three key research questions: factors influencing learning among aging workers, effective learning approaches for this demographic, and strategies for enhancing their learning outcomes. The factors influencing learning were categorized into individual, organizational, and societal dimensions, illustrating the sophisticated interaction that shapes the learning environment. Effective learning approaches identified include lifelong learning, utilizing technology, and intergenerational learning, which are interrelated and reinforce each other. Furthermore, we propose a seven-step socio-technical system approach to enhance learning for the aging workforce. This novel approach considers technological tools, as well as human, organizational, and societal elements that play an essential role in the learning process. Our findings present a comprehensive perspective on the complexities of older workers' learning and offer actionable insights to enhance their learning experience. The proposed socio-technical model contributes to creating an inclusive and supportive learning environment, aiming to boost key areas, such as job performance, satisfaction, health, and well-being. This study's implications extend to organizations aiming to optimize the potential of an aging workforce in a rapidly evolving digital world.

Keywords: Aging; Ageing; Manufacturing and service industries; Learning; Systematic literature review; Sociotechnical system (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:270:y:2024:i:c:s0925527324000501

DOI: 10.1016/j.ijpe.2024.109193

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