Please use this identifier to cite or link to this item: doi:10.22028/D291-41852
Title: Never too late to learn: Unlocking the potential of aging workforce in manufacturing and service industries
Author(s): Ranasinghe, Thilini
Grosse, Eric H.
Glock, Christoph H.
Jaber, Mohamad Y.
Language: English
Title: International Journal of Production Economics
Volume: 270
Publisher/Platform: Elsevier
Year of Publication: 2024
Free key words: Aging
Ageing
Manufacturing and service industries
Learning
Systematic literature review
Sociotechnical system
DDC notations: 330 Economics
Publikation type: Journal Article
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 sevenstep 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.
DOI of the first publication: 10.1016/j.ijpe.2024.109193
URL of the first publication: https://doi.org/10.1016/j.ijpe.2024.109193
Link to this record: urn:nbn:de:bsz:291--ds-418527
hdl:20.500.11880/37448
http://dx.doi.org/10.22028/D291-41852
ISSN: 0925-5273
Date of registration: 5-Apr-2024
Faculty: HW - Fakultät für Empirische Humanwissenschaften und Wirtschaftswissenschaft
Department: HW - Wirtschaftswissenschaft
Professorship: HW - Prof. Dr. Eric Grosse
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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